Senior AI Engineer
Microsoft
Senior AI Engineer
Redmond, Washington, United States
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Overview
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.
Commerce + Ecosystems (C+E) is responsible for enabling and optimizing the end-to-end customer journey on the Microsoft Cloud.
Overview of the role:
We are looking for a Senior AI Engineer to join the The Commerce Financial Platform. The team builds intelligent, scalable services that power Microsoft’s commerce experiences endtoend. We’re accelerating AIdriven business applications—grounded in data, built for collaboration, and designed to simplify complex workflows across CRM/ERP scenarios. As a Senior AI Engineer, you’ll build reliable, responsible AI features that ship to production and are used across Microsoft. r
Qualifications
Required Qualifications:
-
Required/Minimum 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.
- 4+ years of experience in developing and shipping system level features in an enterprise production backend server system.
- 3+ years of experience building and supporting distributed cloud services with production grade.
- 2+ years experience with large language models (LLMs) and generative AI
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/Additional Qualifications
- Master's Degree in Computer Science or related technical field AND 6+ 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 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
- OR equivalent experience.
- Experience with Enterprise Database Management system.
- Experience building Distributed Systems with strong guarantees.
- Understanding of data structures, algorithms, and distributed systems.
- Have experience working collaboratively, solve problems with groups, find win/win solutions and celebrate successes.
- 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
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 $158,400 - $258,000 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
icrosoft will accept applications and processes offers for these roles on an ongoing basis.
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Responsibilities
Responsibilities:
- Design, implement, and ship AI capabilities endtoend—from prototype to production—spanning LLMpowered services, retrieval/grounding pipelines, and robust evaluation/observability.
- Build agentic and toolusing workflows that reason across data and services; optimize for safety, latency, reliability, and cost at cloud scale (Azure preferred).
- Partner with product, research, and platform teams to adapt/finetune models (LLMs/SLMs, multimodal) for real customer scenarios.
- Contribute to service architecture, code quality, testing, and automation; uphold securebydesign and accessibility standards.
- Instrument features with telemetry and offline/online evaluation to drive iterative improvements.
- Participate in oncall/operational excellence as part of a healthy, sustainable engineering culture; mentor peers through reviews and knowledgesharing.