Job description

Overview Microsoft Excel is seeking a Principal Applied Science Manager to lead the science organization advancing agentic AI experiences in Excel. This leader will shape the scientific direction, evaluation strategy, and release readiness of AI agents that help millions of people complete complex spreadsheet tasks from data analysis to model building. The role combines people leadership with deep technical ownership and direct product impact. You will translate frontier AI research into reliable product capabilities, lead frontier model and agent evaluation, and implement evidence-based improvements across quality, latency, reliability, safety, and cost. You will partner closely with engineering, product, design, centralized evaluation teams, other Microsoft AI organizations, and foundation-model providers. In the first year, you will establish a clear Excel Agent science strategy, strengthen model and release-readiness decisions, improve the representativeness and reliability of evaluation systems, accelerate the conversion of research into shipped customer value, and build a resilient organization with clear ownership across critical research and quality workstreams. 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. Responsibilities • Lead, grow, and mentor a multidisciplinary team of researchers and applied scientists. • Set the research and applied-science strategy for agentic AI in Excel. • Drive scientific direction for agent architecture, model and tool selection, prompts, skills, planning, and human-agent collaboration. • Define how agent quality is measured through representative benchmarks, graders, regression suites, and multi-turn evaluations. • Establish release-readiness criteria for new models and agent capabilities. • Lead evaluation and integration of frontier foundation models, balancing quality, latency, reliability, safety, capacity, and cost. • Diagnose agent failures using trajectory analysis, experimentation, and customer-representative scenarios. • Translate research prototypes into production-ready capabilities in partnership with engineering, product management, and design. • Build effective operating mechanisms for model comparisons, quality reviews, research sharing, and technical decision-making. • Develop strong partnerships with internal model teams, research organizations, and external AI laboratories. • Communicate technical findings and recommendations to senior leadership. • Support external research engagement through publications, patents, workshops, and conferences. • Recruit, onboard, and develop research talent while establishing durable technical leadership across the team. Qualifications Required Qualifications: • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research) • OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research) • OR equivalent experience. • 3+ years of people management experience. Other Requirements: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter. Preferred Qualifications: • Advanced degree in Computer Science, AI, Machine Learning, HCI, Software Engineering, or equivalent experience. • Experience leading research and applied science teams focused on LLMs, AI agents, and production AI systems. • Deep knowledge in LLM evaluation, benchmarking, experimentation, failure analysis, and model quality. • Demonstrated technical judgment across agent architectures, prompting, tooling, reliability, safety, latency, and cost. • Track record of translating research innovations into large-scale commercial products. • Experience leading cross-functional initiatives spanning research, engineering, product, and design, while influencing decisions through data and experimentation. • Experience building and evaluating AI agents, model optimization, evaluation infrastructure, and enterprise productivity applications, with recognized technical contributions and strong executive communication skills. #OPG #OPGHiring Applied Sciences M6 - The typical base pay range for this role across the U.S. is USD $165,600 - $296,400 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 $220,800 - $331,200 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: careers.microsoft.com 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.

Requirements

Must-haves

Lead, grow, and mentor a multidisciplinary team of researchers and applied scientists.
Set the research and applied-science strategy for agentic AI in Excel.
Drive scientific direction for agent architecture, model and tool selection, prompts, skills, planning, and human-agent collaboration.
Define how agent quality is measured through representative benchmarks, graders, regression suites, and multi-turn evaluations.
Establish release-readiness criteria for new models and agent capabilities.
Lead evaluation and integration of frontier foundation models, balancing quality, latency, reliability, safety, capacity, and cost.
Diagnose agent failures using trajectory analysis, experimentation, and customer-representative scenarios.
Translate research prototypes into production-ready capabilities in partnership with engineering, product management, and design.
Build effective operating mechanisms for model comparisons, quality reviews, research sharing, and technical decision-making.
Develop strong partnerships with internal model teams, research organizations, and external AI laboratories.
Communicate technical findings and recommendations to senior leadership.
Support external research engagement through publications, patents, workshops, and conferences.
Recruit, onboard, and develop research talent while establishing durable technical leadership across the team.
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience.

Nice-to-haves

Advanced degree in Computer Science, AI, Machine Learning, HCI, Software Engineering, or equivalent experience.
Experience leading research and applied science teams focused on LLMs, AI agents, and production AI systems.
Deep knowledge in LLM evaluation, benchmarking, experimentation, failure analysis, and model quality.
Demonstrated technical judgment across agent architectures, prompting, tooling, reliability, safety, latency, and cost.
Track record of translating research innovations into large-scale commercial products.
Experience leading cross-functional initiatives spanning research, engineering, product, and design, while influencing decisions through data and experimentation.
Experience building and evaluating AI agents, model optimization, evaluation infrastructure, and enterprise productivity applications, with recognized technical contributions and strong executive communication skills.
#OPG #OPGHiring
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Application prep

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