Join the Microsoft Shopping team! We deliver smart shopping experiences with personalization, savings, transparency, and convenience, ensuring confidence in every purchase. Microsoft Shopping is your personal shopping companion, empowering customers to shop smarter and discover what they love. By harnessing the power of AI (artificial intelligence), LLMs (large language models) and LLM-based Agents, we are building best-in-class shopping experiences across Bing, MSN, and Edge. If you are passionate about transforming the online shopping experience for millions of users, this role is for you.

As a Software Engineer II, you will contribute to the development of robust, distributed services, and performance-optimized systems that support Shopping services. You’ll collaborate with different team members to implement features that enhance platform scalability, data modeling, and workflow automation.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.  

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

• Collaborates with appropriate stakeholders to determine user requirements for a scenario.
• Drives identification of dependencies and the development of design documents for a product, application, service, or platform.
• Creates, implements, optimizes, debugs, refactors, and reuses code to establish and improve performance and maintainability, effectiveness, and return on investment (ROI).
• Works collaboratively with other platform, infrastructure, application engineers as well as designers/PMs to build next generation shopping products and services.
• Proactively seeks new knowledge and adapts to new trends, technical solutions, and patterns that will improve the availability, reliability, efficiency, observability, and performance of products while also driving consistency in monitoring and operations at scale.

Required Qualifications:

• Bachelor’s Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience.

Preferred Qualifications:

• Master’s Degree in Computer Science or related technical field AND 3+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR Bachelor’s Degree in Computer Science or related technical field AND 5+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience.
• 2+ years of experience in distributed systems development.
• 2+ years of experience working with microservices.

#MicrosoftAI 

Software Engineering IC3 – The typical base pay range for this role across the U.S. is USD $102,100.00 – $202,200.00 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $133,800.00 – $219,200.00 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Advertising serves billions of ad decisions every day across search, native, shopping, display, audience, and AI-powered advertising experiences. Trust & Safety is foundational to this marketplace: protecting users from harmful, deceptive, and low-quality content; protecting advertisers, publishers, and partners from fraud and abuse; and ensuring Microsoft Ads operates with strong policy, privacy, security, compliance, and regulatory integrity.We are seeking a deeply technical Senior Principal Architects to define and drive the next generation of the Ads Trust & Safety AI Platform. This is a engineering leadership role that entails setting technical direction, shaping platform strategy, influencing multiple engineering and science teams, and building durable systems that compound across Trust & Safety, Risk, Fraud, Security, Policy, Measurement, and Enforcement. This role is for a hands-on technical leader who can combine large-scale platform engineering with modern AI systems: agentic investigation workflows, LLM-powered reasoning, retrieval and evidence generation, heterogeneous model serving, risk intelligence, human-in-the-loop review, and high-integrity decisioning.The platform will power how Microsoft Ads understands advertisers, domains, landing pages, websites, business entities, policy risk, fraud signals, and adversarial behavior. It will enable faster and more reliable enforcement decisions, richer evidence for reviewers and investigators, safer automation, and stronger marketplace protection. A key part of this role is collaboration across the broader Trust ecosystem: Microsoft Ads, Microsoft Trust and Safety teams across products, Security,  Identity, and relevant worldwide industry peers and partners. The role requires someone who can evangelize technical direction, learn from adjacent teams and industry practices, align standards, and convert shared learnings into production-grade platform capabilities.

AI Platform Architecture and Technical Strategy

• Define the long-term architecture for the Ads Trust & Safety AI Platform across ingestion, signal acquisition, entity intelligence, retrieval, model orchestration, agentic workflows, decisioning, enforcement, human review, audit, and measurement.
• Translate broad Trust & Safety, Risk, Fraud, Security, and Policy needs into reusable platform capabilities.
• Establish reference architectures, design principles, technical standards, and engineering patterns for high-integrity AI and decisioning systems.
• Drive architecture choices across latency, throughput, quality, cost, explainability, governance, reliability, and operational safety.
• Identify critical platform gaps and create a roadmap that balances near-term delivery with long-term leverage.

Deep Research Agents and AI-Assisted Investigation

• Architect platform for Deep Research Agents that investigate domains, landing pages, advertisers, business entities, ownership patterns, web presence, reputation, policy risk, and fraud signals.
• Architect workflows that combine retrieval, crawling, structured evidence extraction, LLM reasoning, policy grounding, risk scoring and human in the loop.
• Architect guardrails for agentic systems, including source provenance, confidence scoring, hallucination controls, audit logs, escalation paths, and human override.
• Partner with Applied Science to convert AI research prototypes into production systems with clear quality, latency, cost, reliability, safety, and governance targets.

Entity Intelligence, Decisioning, and Enforcement

• Architect systems for high-fidelity understanding of domains, websites, landing pages, advertisers, business identities, ownership structures, relationship graphs, reputation, and provenance.
• Design real-time, nearline, and batch scoring systems for policy enforcement, fraud detection, abuse prevention, advertiser risk scoring, and marketplace protection.
• Evolve abstractions for model orchestration, feature lookup, signal stores, retrieval, model versioning, decision logging, policy controls, fallbacks, and experimentation.

Security, Risk, and Fraud Platform

• Architect systems to detect , learn and mitigate adversarial behavior across the advertiser lifecycle, including account creation, login events, payment changes, budget changes, campaign edits, creative changes, landing-page changes, and enforcement history.
• Build sequential and event-based risk systems that reason over advertiser behavior over time rather than treating each decision as an isolated event.

Cross-Microsoft Collaboration, Industry Learning, and Technical Leadership

• Collaborate across wider Microsoft , Safety, Security, Responsible AI, Identity and partner teams to create shared platform capabilities for risk detection, abuse prevention, evidence generation, and enforcement governance.
• Evangelize a coherent Trust & Safety AI platform strategy across Microsoft, helping teams converge on shared architectures, reusable abstractions, common taxonomies, and consistent decisioning patterns.
• Evangelize  & Learn from industry peers, and approved partner networks facing similar scale abuse patterns, and translate those learnings into practical platform improvements.

• Bachelor’s Degree in Computer Science or related technical field AND 15+ years of professional software engineering experience, or equivalent practical experience.8+ years of senior technical leadership experience influencing engineers, technical leads, architects, applied scientists, or cross-functional engineering teams across complex platform or product areas.
• Proven experience architecting and delivering large-scale production systems with meaningful reliability, scalability, latency, correctness, availability, security, and operational requirements.
• Deep technical experience in one or more of the following platform areas: AI/ML systems, agentic systems, model-serving infrastructure, decisioning systems, distributed systems, data platforms, workflow platforms, risk platforms, security platforms, or Trust & Safety systems.
• Experience building or technically leading production AI/ML systems, including exposure to modern AI patterns such as LLM-based workflows, retrieval-augmented generation, model orchestration, automated reasoning, human-in-the-loop systems, AI-assisted operational tooling, or agentic workflows.
• Strong understanding of the engineering requirements for deploying AI or decision systems in production, including evaluation, observability, quality measurement, rollout safety, fallback behavior, latency/cost tradeoffs, drift detection, explainability, governance, and operational reliability.
• Experience designing high-integrity systems where decisions must be auditable, reproducible, explainable, governed, and secure, especially when handling sensitive signals, advertiser impact, policy enforcement, risk decisions, or compliance-sensitive workflows.
• Ability to drive clarity from ambiguity, define technical direction, create reusable platform abstractions, and influence execution across multiple teams without relying on direct management authority.
• Strong written and verbal communication skills, including the ability to explain architecture, tradeoffs, risks, sequencing, and technical strategy to senior engineering, science, product, policy, security, and business leaders.

Preferred Qualification
The candidate is not expected to have deep experience in every area below. Broader coverage across these areas is preferred, especially where the candidate has demonstrated the ability to connect multiple domains into durable platform architecture and production systems.

• Deep domain experience in Trust & Safety, Fraud, Abuse, Risk, Security, Ads Quality, Marketplace Integrity, Policy Enforcement, or advertiser protection systems.Experience with adversarial systems, including phishing, malware, cloaking, account takeover, payment abuse, fake identities, compromised advertisers, coordinated fraud, and policy evasion.
• Experience building Deep Research Agents, investigation agents, reviewer-assist systems, retrieval-augmented generation systems, LLM-powered operational workflows, or AI systems that produce grounded evidence for human or automated decisions.
• Expertise in heterogeneous inference platforms supporting LLMs, SLMs, wide & deep models, ensembles, graph models, classical ML models, heuristics, and rules engines.
• Experience with entity intelligence, knowledge graphs, web crawling, domain reputation, business identity resolution, provenance, evidence extraction, or risk scoring.
• Experience designing human-in-the-loop review systems, appeals workflows, audit platforms, policy reasoning systems, or enforcement governance mechanisms.
• Experience with large-scale measurement systems for false positives, false negatives, model drift, agent quality, policy quality, reviewer quality, enforcement stability, business impact, and operational health.
• Experience collaborating with Trust, Safety, Security, Privacy, Identity, Compliance, Legal, or Responsible AI teams across multiple products or platforms.
• Experience evangelizing technical strategy across multiple teams, learning from industry peers, and helping establish shared standards, taxonomies, schemas, signal-quality measures, or platform patterns.
• Experience working with industry partners, trusted abuse-prevention networks, threat-intelligence providers, domain-reputation providers, identity-verification providers, payment-risk partners, or ecosystem safety initiatives. 

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Advertising serves billions of ad decisions every day across search, native, shopping, display, audience, and AI-powered advertising experiences. Trust & Safety is foundational to this marketplace: protecting users from harmful, deceptive, and low-quality content; protecting advertisers, publishers, and partners from fraud and abuse; and ensuring Microsoft Ads operates with strong policy, privacy, security, compliance, and regulatory integrity.We are seeking a deeply technical Senior Principal Architects to define and drive the next generation of the Ads Trust & Safety AI Platform. This is a engineering leadership role that entails setting technical direction, shaping platform strategy, influencing multiple engineering and science teams, and building durable systems that compound across Trust & Safety, Risk, Fraud, Security, Policy, Measurement, and Enforcement. This role is for a hands-on technical leader who can combine large-scale platform engineering with modern AI systems: agentic investigation workflows, LLM-powered reasoning, retrieval and evidence generation, heterogeneous model serving, risk intelligence, human-in-the-loop review, and high-integrity decisioning.The platform will power how Microsoft Ads understands advertisers, domains, landing pages, websites, business entities, policy risk, fraud signals, and adversarial behavior. It will enable faster and more reliable enforcement decisions, richer evidence for reviewers and investigators, safer automation, and stronger marketplace protection. A key part of this role is collaboration across the broader Trust ecosystem: Microsoft Ads, Microsoft Trust and Safety teams across products, Security,  Identity, and relevant worldwide industry peers and partners. The role requires someone who can evangelize technical direction, learn from adjacent teams and industry practices, align standards, and convert shared learnings into production-grade platform capabilities.

AI Platform Architecture and Technical Strategy

• Define the long-term architecture for the Ads Trust & Safety AI Platform across ingestion, signal acquisition, entity intelligence, retrieval, model orchestration, agentic workflows, decisioning, enforcement, human review, audit, and measurement.
• Translate broad Trust & Safety, Risk, Fraud, Security, and Policy needs into reusable platform capabilities.
• Establish reference architectures, design principles, technical standards, and engineering patterns for high-integrity AI and decisioning systems.
• Drive architecture choices across latency, throughput, quality, cost, explainability, governance, reliability, and operational safety.
• Identify critical platform gaps and create a roadmap that balances near-term delivery with long-term leverage.

Deep Research Agents and AI-Assisted Investigation

• Architect platform for Deep Research Agents that investigate domains, landing pages, advertisers, business entities, ownership patterns, web presence, reputation, policy risk, and fraud signals.
• Architect workflows that combine retrieval, crawling, structured evidence extraction, LLM reasoning, policy grounding, risk scoring and human in the loop.
• Architect guardrails for agentic systems, including source provenance, confidence scoring, hallucination controls, audit logs, escalation paths, and human override.
• Partner with Applied Science to convert AI research prototypes into production systems with clear quality, latency, cost, reliability, safety, and governance targets.

Entity Intelligence, Decisioning, and Enforcement

• Architect systems for high-fidelity understanding of domains, websites, landing pages, advertisers, business identities, ownership structures, relationship graphs, reputation, and provenance.
• Design real-time, nearline, and batch scoring systems for policy enforcement, fraud detection, abuse prevention, advertiser risk scoring, and marketplace protection.
• Evolve abstractions for model orchestration, feature lookup, signal stores, retrieval, model versioning, decision logging, policy controls, fallbacks, and experimentation.

Security, Risk, and Fraud Platform

• Architect systems to detect , learn and mitigate adversarial behavior across the advertiser lifecycle, including account creation, login events, payment changes, budget changes, campaign edits, creative changes, landing-page changes, and enforcement history.
• Build sequential and event-based risk systems that reason over advertiser behavior over time rather than treating each decision as an isolated event.

Cross-Microsoft Collaboration, Industry Learning, and Technical Leadership

• Collaborate across wider Microsoft , Safety, Security, Responsible AI, Identity and partner teams to create shared platform capabilities for risk detection, abuse prevention, evidence generation, and enforcement governance.
• Evangelize a coherent Trust & Safety AI platform strategy across Microsoft, helping teams converge on shared architectures, reusable abstractions, common taxonomies, and consistent decisioning patterns.
• Evangelize  & Learn from industry peers, and approved partner networks facing similar scale abuse patterns, and translate those learnings into practical platform improvements.

• Bachelor’s Degree in Computer Science or related technical field AND 15+ years of professional software engineering experience, or equivalent practical experience.8+ years of senior technical leadership experience influencing engineers, technical leads, architects, applied scientists, or cross-functional engineering teams across complex platform or product areas.
• Proven experience architecting and delivering large-scale production systems with meaningful reliability, scalability, latency, correctness, availability, security, and operational requirements.
• Deep technical experience in one or more of the following platform areas: AI/ML systems, agentic systems, model-serving infrastructure, decisioning systems, distributed systems, data platforms, workflow platforms, risk platforms, security platforms, or Trust & Safety systems.
• Experience building or technically leading production AI/ML systems, including exposure to modern AI patterns such as LLM-based workflows, retrieval-augmented generation, model orchestration, automated reasoning, human-in-the-loop systems, AI-assisted operational tooling, or agentic workflows.
• Strong understanding of the engineering requirements for deploying AI or decision systems in production, including evaluation, observability, quality measurement, rollout safety, fallback behavior, latency/cost tradeoffs, drift detection, explainability, governance, and operational reliability.
• Experience designing high-integrity systems where decisions must be auditable, reproducible, explainable, governed, and secure, especially when handling sensitive signals, advertiser impact, policy enforcement, risk decisions, or compliance-sensitive workflows.
• Ability to drive clarity from ambiguity, define technical direction, create reusable platform abstractions, and influence execution across multiple teams without relying on direct management authority.
• Strong written and verbal communication skills, including the ability to explain architecture, tradeoffs, risks, sequencing, and technical strategy to senior engineering, science, product, policy, security, and business leaders.

Preferred Qualification
The candidate is not expected to have deep experience in every area below. Broader coverage across these areas is preferred, especially where the candidate has demonstrated the ability to connect multiple domains into durable platform architecture and production systems.

• Deep domain experience in Trust & Safety, Fraud, Abuse, Risk, Security, Ads Quality, Marketplace Integrity, Policy Enforcement, or advertiser protection systems.Experience with adversarial systems, including phishing, malware, cloaking, account takeover, payment abuse, fake identities, compromised advertisers, coordinated fraud, and policy evasion.
• Experience building Deep Research Agents, investigation agents, reviewer-assist systems, retrieval-augmented generation systems, LLM-powered operational workflows, or AI systems that produce grounded evidence for human or automated decisions.
• Expertise in heterogeneous inference platforms supporting LLMs, SLMs, wide & deep models, ensembles, graph models, classical ML models, heuristics, and rules engines.
• Experience with entity intelligence, knowledge graphs, web crawling, domain reputation, business identity resolution, provenance, evidence extraction, or risk scoring.
• Experience designing human-in-the-loop review systems, appeals workflows, audit platforms, policy reasoning systems, or enforcement governance mechanisms.
• Experience with large-scale measurement systems for false positives, false negatives, model drift, agent quality, policy quality, reviewer quality, enforcement stability, business impact, and operational health.
• Experience collaborating with Trust, Safety, Security, Privacy, Identity, Compliance, Legal, or Responsible AI teams across multiple products or platforms.
• Experience evangelizing technical strategy across multiple teams, learning from industry peers, and helping establish shared standards, taxonomies, schemas, signal-quality measures, or platform patterns.
• Experience working with industry partners, trusted abuse-prevention networks, threat-intelligence providers, domain-reputation providers, identity-verification providers, payment-risk partners, or ecosystem safety initiatives. 

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Advertising serves billions of ad decisions every day across search, native, shopping, display, audience, and AI-powered advertising experiences. Trust & Safety is foundational to this marketplace: protecting users from harmful, deceptive, and low-quality content; protecting advertisers, publishers, and partners from fraud and abuse; and ensuring Microsoft Ads operates with strong policy, privacy, security, compliance, and regulatory integrity.We are seeking a deeply technical Senior Principal Architects to define and drive the next generation of the Ads Trust & Safety AI Platform. This is a engineering leadership role that entails setting technical direction, shaping platform strategy, influencing multiple engineering and science teams, and building durable systems that compound across Trust & Safety, Risk, Fraud, Security, Policy, Measurement, and Enforcement. This role is for a hands-on technical leader who can combine large-scale platform engineering with modern AI systems: agentic investigation workflows, LLM-powered reasoning, retrieval and evidence generation, heterogeneous model serving, risk intelligence, human-in-the-loop review, and high-integrity decisioning.The platform will power how Microsoft Ads understands advertisers, domains, landing pages, websites, business entities, policy risk, fraud signals, and adversarial behavior. It will enable faster and more reliable enforcement decisions, richer evidence for reviewers and investigators, safer automation, and stronger marketplace protection. A key part of this role is collaboration across the broader Trust ecosystem: Microsoft Ads, Microsoft Trust and Safety teams across products, Security,  Identity, and relevant worldwide industry peers and partners. The role requires someone who can evangelize technical direction, learn from adjacent teams and industry practices, align standards, and convert shared learnings into production-grade platform capabilities.

AI Platform Architecture and Technical Strategy

• Define the long-term architecture for the Ads Trust & Safety AI Platform across ingestion, signal acquisition, entity intelligence, retrieval, model orchestration, agentic workflows, decisioning, enforcement, human review, audit, and measurement.
• Translate broad Trust & Safety, Risk, Fraud, Security, and Policy needs into reusable platform capabilities.
• Establish reference architectures, design principles, technical standards, and engineering patterns for high-integrity AI and decisioning systems.
• Drive architecture choices across latency, throughput, quality, cost, explainability, governance, reliability, and operational safety.
• Identify critical platform gaps and create a roadmap that balances near-term delivery with long-term leverage.

Deep Research Agents and AI-Assisted Investigation

• Architect platform for Deep Research Agents that investigate domains, landing pages, advertisers, business entities, ownership patterns, web presence, reputation, policy risk, and fraud signals.
• Architect workflows that combine retrieval, crawling, structured evidence extraction, LLM reasoning, policy grounding, risk scoring and human in the loop.
• Architect guardrails for agentic systems, including source provenance, confidence scoring, hallucination controls, audit logs, escalation paths, and human override.
• Partner with Applied Science to convert AI research prototypes into production systems with clear quality, latency, cost, reliability, safety, and governance targets.

Entity Intelligence, Decisioning, and Enforcement

• Architect systems for high-fidelity understanding of domains, websites, landing pages, advertisers, business identities, ownership structures, relationship graphs, reputation, and provenance.
• Design real-time, nearline, and batch scoring systems for policy enforcement, fraud detection, abuse prevention, advertiser risk scoring, and marketplace protection.
• Evolve abstractions for model orchestration, feature lookup, signal stores, retrieval, model versioning, decision logging, policy controls, fallbacks, and experimentation.

Security, Risk, and Fraud Platform

• Architect systems to detect , learn and mitigate adversarial behavior across the advertiser lifecycle, including account creation, login events, payment changes, budget changes, campaign edits, creative changes, landing-page changes, and enforcement history.
• Build sequential and event-based risk systems that reason over advertiser behavior over time rather than treating each decision as an isolated event.

Cross-Microsoft Collaboration, Industry Learning, and Technical Leadership

• Collaborate across wider Microsoft , Safety, Security, Responsible AI, Identity and partner teams to create shared platform capabilities for risk detection, abuse prevention, evidence generation, and enforcement governance.
• Evangelize a coherent Trust & Safety AI platform strategy across Microsoft, helping teams converge on shared architectures, reusable abstractions, common taxonomies, and consistent decisioning patterns.
• Evangelize  & Learn from industry peers, and approved partner networks facing similar scale abuse patterns, and translate those learnings into practical platform improvements.

• Bachelor’s Degree in Computer Science or related technical field AND 15+ years of professional software engineering experience, or equivalent practical experience.8+ years of senior technical leadership experience influencing engineers, technical leads, architects, applied scientists, or cross-functional engineering teams across complex platform or product areas.
• Proven experience architecting and delivering large-scale production systems with meaningful reliability, scalability, latency, correctness, availability, security, and operational requirements.
• Deep technical experience in one or more of the following platform areas: AI/ML systems, agentic systems, model-serving infrastructure, decisioning systems, distributed systems, data platforms, workflow platforms, risk platforms, security platforms, or Trust & Safety systems.
• Experience building or technically leading production AI/ML systems, including exposure to modern AI patterns such as LLM-based workflows, retrieval-augmented generation, model orchestration, automated reasoning, human-in-the-loop systems, AI-assisted operational tooling, or agentic workflows.
• Strong understanding of the engineering requirements for deploying AI or decision systems in production, including evaluation, observability, quality measurement, rollout safety, fallback behavior, latency/cost tradeoffs, drift detection, explainability, governance, and operational reliability.
• Experience designing high-integrity systems where decisions must be auditable, reproducible, explainable, governed, and secure, especially when handling sensitive signals, advertiser impact, policy enforcement, risk decisions, or compliance-sensitive workflows.
• Ability to drive clarity from ambiguity, define technical direction, create reusable platform abstractions, and influence execution across multiple teams without relying on direct management authority.
• Strong written and verbal communication skills, including the ability to explain architecture, tradeoffs, risks, sequencing, and technical strategy to senior engineering, science, product, policy, security, and business leaders.

Preferred Qualification
The candidate is not expected to have deep experience in every area below. Broader coverage across these areas is preferred, especially where the candidate has demonstrated the ability to connect multiple domains into durable platform architecture and production systems.

• Deep domain experience in Trust & Safety, Fraud, Abuse, Risk, Security, Ads Quality, Marketplace Integrity, Policy Enforcement, or advertiser protection systems.Experience with adversarial systems, including phishing, malware, cloaking, account takeover, payment abuse, fake identities, compromised advertisers, coordinated fraud, and policy evasion.
• Experience building Deep Research Agents, investigation agents, reviewer-assist systems, retrieval-augmented generation systems, LLM-powered operational workflows, or AI systems that produce grounded evidence for human or automated decisions.
• Expertise in heterogeneous inference platforms supporting LLMs, SLMs, wide & deep models, ensembles, graph models, classical ML models, heuristics, and rules engines.
• Experience with entity intelligence, knowledge graphs, web crawling, domain reputation, business identity resolution, provenance, evidence extraction, or risk scoring.
• Experience designing human-in-the-loop review systems, appeals workflows, audit platforms, policy reasoning systems, or enforcement governance mechanisms.
• Experience with large-scale measurement systems for false positives, false negatives, model drift, agent quality, policy quality, reviewer quality, enforcement stability, business impact, and operational health.
• Experience collaborating with Trust, Safety, Security, Privacy, Identity, Compliance, Legal, or Responsible AI teams across multiple products or platforms.
• Experience evangelizing technical strategy across multiple teams, learning from industry peers, and helping establish shared standards, taxonomies, schemas, signal-quality measures, or platform patterns.
• Experience working with industry partners, trusted abuse-prevention networks, threat-intelligence providers, domain-reputation providers, identity-verification providers, payment-risk partners, or ecosystem safety initiatives. 

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Join the “Microsoft AI Web Data Platform Team” as a Principal Software Engineer, in a technical leadership capacity, to architect platforms and deliver Internet scale web documents, with full richness to Ground LLMs for 1st party Copilots and 3rd party AI solutions.

In this role, you’ll play a key role in building large scale platforms that are fundamental to Bing Search, AI Grounding and Microsoft AI training driving transformative scenarios powering massive scale of users while processing tens of billions of documents per day and managing hundreds of petabytes of data. A suitable candidate will bring a blend of expertise in large-scale data platforms & AI.

In today’s AI-driven world, where data is more valuable than ever, we’re embarking on an exciting mission to elevate our platform, harnessing additional richness to position it as the integral building block of AI solutions across the industry. If you’re passionate about building high-performance systems that shape the future of data platforms that power AI solutions, this is the place for you!

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

• Align team efforts with business and user requirements by collaborating with stakeholders to define priorities, resolve dependencies, and ensure delivery of well-documented design and implementation plans for products, applications, services, or platforms.
• Guide system design and architectural decisions across multiple components, encouraging the use of data and telemetry to make informed decisions.
• Drive engineering excellence by fostering a culture of building modular, secure, reliable, testable, maintainable, and reusable solutions, while promoting active monitoring practices.
• Establish quality assurance strategies by setting standards for improving test coverage, streamlining integration testing, and addressing critical problem areas proactively.
• Oversee and improve operational reliability, guiding efforts to troubleshoot and optimize automation, monitoring, and Live Site health. 

Required Qualifications:

• Bachelor’s Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience.

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Business Support ATR-E – The typical base pay range for this role across the U.S. is USD $33.89 – $67.16 per hour. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $45.67 – $73.65 per hour.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft AI (MAI) is building the next generation of AI-powered consumer experiences across Microsoft products, connecting people to information, entertainment, shopping, and productivity through intelligent, personalized experiences. MSN and Copilot Discover are at the center of this vision, helping millions of users discover relevant content, stay informed, and engage with the web in meaningful ways.

The MSN & Copilot Discover Business Analytics team serves as a horizontal analytics team supporting multiple product, engineering, marketplace, monetization, and business teams across the ecosystem. We are responsible for driving business insights, forecasting, strategic planning, experimentation, monetization analytics, and decision-making frameworks that influence product investments and business outcomes at scale.

We are seeking an experienced Principal Business Analytics Data Scientist with solid business acumen, deep analytical expertise, and experience in content platforms, digital advertising, and monetization. This role offers a unique opportunity to work at the intersection of user engagement, AI-powered content discovery, and revenue optimization while partnering closely with product teams, MAI Marketplace, Monetization, Finance, and Engineering organizations.

The ideal candidate combines rigorous analytical thinking with a solid understanding of content ecosystems, advertising marketplaces, user engagement, forecasting, experimentation, and business strategy. They are comfortable navigating ambiguity, influencing senior stakeholders, and translating complex data into actionable business decisions.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.  

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

• Serve as a trusted analytics partner to leadership and cross-functional teams, translating data into clear business recommendations.
• Partner with Product, Engineering, MAI Marketplace, Monetization, Finance, and Business Planning teams to shape strategy and investment decisions.
• Analyze user engagement, content consumption, marketplace dynamics, and revenue performance to identify growth opportunities and business risks.
• Develop business frameworks that connect product initiatives, user behavior, content quality, and monetization outcomes.
• Build forecasting and scenario-planning models for engagement, traffic, ad requests, and revenue.
• Leverage AI and machine learning solutions to automate business insights, improve forecasting accuracy, enhance decision-making processes, and scale analytical capabilities across the organization.
• Evaluate tradeoffs between user experience, engagement, and monetization to support long-term business growth.
• Communicate insights clearly to senior stakeholders and influence decisions through data-driven storytelling.

Required Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Master’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Bachelor’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience.

Preferred Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Master’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Bachelor’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience.
• Experience in content ecosystems, news feeds, recommendation systems, search, shopping, or content discovery platforms.
• Experience partnering with advertising, monetization, or marketplace organizations.
• Familiarity with key engagement and monetization metrics such as sessions, time spent, retention, RPM, ad requests, inventory utilization, advertiser demand, and marketplace efficiency.
• Experience leading analytics for large-scale consumer products with millions of users.
• Demonstrated success influencing product strategy and business outcomes through data-driven insights.
• Solid understanding of AI-powered consumer experiences and their impact on user engagement and monetization.
• Experience managing cross-functional initiatives involving Product, Engineering, Monetization, Marketplace, and Finance stakeholders.

#MicrosoftAI #BusinessAnalytics #DataScientist #MAI #Copilot #Monitization

Data Science IC5 – The typical base pay range for this role across the U.S. is USD $142,800 – $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 – $304,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

We have an opportunity to fundamentally rethink the software that people use most: the browser. Every day, billions of people open a browser because they want something. They want to buy something, learn something, get something done, figure something out. The browser is where intent becomes action.

For decades, that journey has been mostly unchanged: you search, you click, you read, you navigate. AI changes the fundamental equation. The distance between what someone wants and what they actually accomplish can shrink dramatically — and the browser is where that happens for billions of people.

We’re looking for a Principal Product Manager who sees that opportunity clearly and has the conviction and the hands to go build it. Someone who invents on behalf of customers rather than waiting to be told what they want. Someone who thinks about AI not just as a set of features to add, but as the means by which we rethink the whole product on behalf of the people who use it every day. The role is yours to define. The surface area is massive. The moment is now.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.  

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

• Own the AI-native product strategy for Microsoft Edge, defining how AI collapses the distance between what people want and what they can accomplish — across research, tasks, decisions, and everything else people bring to their browser.
• Invent on behalf of billions of users: form solid, well-reasoned convictions about what people need before they can articulate it themselves, and build toward that vision.
• Turn frontier AI capabilities into experiences customers actually want to use, not demos that impress in a conference room and disappear six months later.
• Run fast, hypothesis-driven experimentation cycles across new AI interaction patterns and UI flows; let real usage data sharpen your convictions.
• Partner with research teams to identify model advances with real customer value and move them from research to shipped product.
• Work with data science and growth teams to ensure AI-powered features reach and retain the users who need them most.
• Set clear direction in ambiguous spaces, make tradeoffs visible to leadership, and drive alignment across partner teams.
• Operate as a senior IC: coach PMs on adjacent workstreams, unblock critical path items, and hold a high bar for what “done” means.

Required Qualifications:

• Bachelor’s Degree AND 8+ years experience in product/service/program management or software development
  • OR equivalent experience.

Preferred Qualifications:

• Bachelor’s Degree AND 12+ years experience in product/service/program management or software development
  • OR equivalent experience.
• 5+ years shipping consumer products at meaningful scale.
• 3+ years building products with large language models, agentic AI, or similar frontier AI technologies.
• You have built a product from 0 to launch with your own hands. Not contributed to someone else’s initiative — owned it, defined the scope, recruited the help, made the calls, and shipped it.
• A track record of turning complex, ambiguous technical capabilities into products customers love and return to.
• Ability to lead and align multiple teams through long, cross-functional delivery cycles.
• Solid product intuition and the conviction to act on it, even when the data is incomplete.
• Familiarity with prompting patterns, RAG, agentic frameworks, or eval-based quality measurement.
• Experience with browser technologies, web platform, or Chromium-based products.
• A genuine interest in emerging AI research and a habit of thinking beyond established playbooks.
• Experience working with geographically distributed engineering teams.

#MicrosoftAI 

Product Management IC5 – The typical base pay range for this role across the U.S. is USD $142,800 – $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 – $304,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

The Bing Places team is building intelligence that powers local search experiences used by millions of people every day. We are looking for Applied Scientists to help design, build, and ship advanced AI and machine learning solutions—spanning large language models (LLMs), retrieval augmented generation (RAG), learning‑to‑ranking, and entity understanding—to deliver high‑quality, trustworthy local search experiences at scale.

As an Applied Scientist on Bing Places,

• You will work on challenging problems that require deep technical expertise and a strong focus on real‑world impact.
• You will work end‑to‑end: from problem formulation and data analysis, through model development and experimentation, to production deployment and live flighting.
• You will collaborate closely with engineering and product partners to develop, experiment with, and ship models that operate at Microsoft scale, while contributing to the broader scientific community through publications and patents

Bing Location Understanding and Geocoding team – (Redmond, WA)

The Bing Location Understanding (BLU) and Bing Geocoding (BingGC) teams build the core intelligence that powers location interpretation, address understanding, and geospatial reasoning across Bing, Maps, and downstream Microsoft experiences. Our systems operate at global scale and combine machine learning, natural language understanding, ranking, and large‑scale data processing to deliver high‑quality results in real time.

• Formulate complex product and engineering problems as machine learning and AI tasks, and drive them from concept through production
• Design, implement, and evaluate ML‑ and LLM‑based models that improve Bing Places quality, relevance, and coverage
• Conduct rigorous data analysis to understand system behavior, identify opportunities, and define success metrics
• Prototype new modeling approaches and iterate quickly based on offline evaluation and online experimentation
• Own experimentation pipelines, including offline validation and large‑scale online A/B flighting
• Partner closely with engineers to integrate models into production systems and ensure long‑term reliability and performance
• Drive technical direction within your problem space and influence broader modeling and platform decisions
• Document and communicate results through technical design reviews, papers, and patent filings

Preferred Qualifications: 

• Master’s degree or PhD in a relevant technical field
• 4+ years of experience applying AI solutions or LLMs to real‑world systems (RAG, ranking, classification, reasoning)
• Proven expertise in machine learning, statistical methods, and data‑driven problem solving
• Hands‑on experience developing and evaluating models on large‑scale, real‑world datasets
• Proficiency in Python and experience with modern ML frameworks (e.g., PyTorch, TensorFlow, JAX, or similar)
• Understanding of experimentation methodologies, including offline metrics and online A/B testing
• Ability to independently scope problems and deliver high‑quality solutions in ambiguous environments
• Strong collaboration skills and experience working with engineering and product partners
• Ability to clearly communicate technical concepts and trade‑offs to both technical and non‑technical audiences

• Background in search, information retrieval, knowledge graphs, or local/entity understanding
• Track record of publications or granted/pending patents
• Familiarity with distributed training, model optimization, and production ML infrastructure
• Comfort operating across the full lifecycle—from research and prototyping to production and live operations

Applied Sciences IC3 – The typical base pay range for this role across the U.S. is USD $102,100.00 – $202,200.00 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $133,800.00 – $219,200.00 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.