Job description

Overview The Foundry IQ team is building the next generation of agentic knowledge retrieval combining enterprise knowledge with AI agents at scale. We are expanding Azure AI Search to address complex queries that require refinement, reasoning, and reflection, delivering high-quality, grounded results for both people and large language models. Our customers span a wide range of industries, data volumes, and mission-critical scenarios. In this role, you will: • Design, build, and operate scalable backend services that integrate with internal and external language models. • Partner closely with Applied Science to turn research advances into reliable production capabilities. • Develop GPU-backed integrations that support large-scale production machine learning workloads. • Evaluate end-to-end production systems to ensure the quality, reliability, and performance of AI-powered experiences. • Advance knowledge retrieval and data-layer AI integration, including RAG, agentic retrieval, and LLM context engineering. • Determine where advanced reasoning models provide the most value and integrate low-latency models where speed is critical. • Work directly with customers and partner teams to solve challenging retrieval and AI problems. You will collaborate with a multidisciplinary team of engineers, applied scientists, and product leaders, as well as teams across Microsoft—including Bing, Fabric, Work IQ, and Microsoft Research. We value diverse perspectives, customer obsession, technical excellence, trust, and close collaboration. The ideal candidate combines strong distributed-systems experience with practical expertise in machine learning infrastructure, GPU-hosted model integration, and LLM context engineering. You should be comfortable partnering with Applied Science, navigating ambiguous technical challenges, and translating emerging AI capabilities into secure, dependable, and low-latency services at cloud scale. If you are excited to work at the forefront of AI, improve how customers discover and use knowledge, and build globally distributed experiences on one of the world’s largest cloud platforms, the Foundry IQ team may be the right place for you. Responsibilities • Design, build, and maintain Azure backend services and associated APIs. • Partner with Applied Science to bring high quality prompts, ML models and pre and post processing components into production in a secure, reliable, and scalable way. • Work directly with GPUs to support production ML workloads at scale. • Providing evaluation tooling and support of production integrations to ensure end-to-end AI quality of Applied Science deliverables. • Contribute to team plans, documents, and communication in a clear and efficient way. Qualifications Required Qualifications • Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent 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 Preferred Qualifications • Development of Azure Services with full understanding of service release and live-site responsibilities. • Coding in C# and Python in a production system. • Ability to move fast while ensuring quality at scale in a collaborative team setting. • Development experience with large language models. • Development experience with GPU based models and model hosting. • 2+ years’ experience developing and deploying live production systems as part of a product team. • Coding in C++ or Java in a production system. • Excellent hybrid work skills – clear synchronous and asynchronous communication, strong teamwork, and collaboration skills • Customer focused, strategic, drives for results, is self-motivated, and has a propensity for action. • Problem solver: ability to solve problems that the world has not solved before. Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $160,200 - $261,000 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

The Foundry IQ team is building the next generation of agentic knowledge retrieval combining enterprise knowledge with AI agents at scale.
Design, build, and operate scalable backend services that integrate with internal and external language models.
Partner closely with Applied Science to turn research advances into reliable production capabilities.
Develop GPU-backed integrations that support large-scale production machine learning workloads.
Evaluate end-to-end production systems to ensure the quality, reliability, and performance of AI-powered experiences.
Advance knowledge retrieval and data-layer AI integration, including RAG, agentic retrieval, and LLM context engineering.
Determine where advanced reasoning models provide the most value and integrate low-latency models where speed is critical.
Work directly with customers and partner teams to solve challenging retrieval and AI problems.
Design, build, and maintain Azure backend services and associated APIs.
Partner with Applied Science to bring high quality prompts, ML models and pre and post processing components into production in a secure, reliable, and scalable way.
Work directly with GPUs to support production ML workloads at scale.
Providing evaluation tooling and support of production integrations to ensure end-to-end AI quality of Applied Science deliverables.
Contribute to team plans, documents, and communication in a clear and efficient way.
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:

Nice-to-haves

Development of Azure Services with full understanding of service release and live-site responsibilities.
Coding in C# and Python in a production system.
Ability to move fast while ensuring quality at scale in a collaborative team setting.
Development experience with large language models.
Development experience with GPU based models and model hosting.
Coding in C++ or Java in a production system.
Excellent hybrid work skills – clear synchronous and asynchronous communication, strong teamwork, and collaboration skills
Customer focused, strategic, drives for results, is self-motivated, and has a propensity for action.
Problem solver: ability to solve problems that the world has not solved before.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiazuremachine learningllmmljavajavascriptpython

Platform: eightfold
Effort: medium