Principal AI Engineer

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 Principal AI Engineer to join the Commerce Financial Platform organization. The team builds intelligent, scalable services & experiences that power Microsoft’s commerce needs end-to-end. We’re accelerating a new era of AI driven business applications—grounded in data, built for collaboration, and designed to simplify complex workflows across CRM/ERP scenarios. If you’re excited to shape how people interact with AI at enterprise scale, continuously improve processes and deliver products   

Required Qualifications:

• ​​Bachelor'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 equivalent experience.​
• 4+ years experience with large language models (LLMs) and generative AI

Preferred Qualifications:

• ​​Master'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 Bachelor's Degree in Computer Science or related technical field AND 12+ 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 agentic systems, model/tool orchestration, and/or retrieval augmented generation (RAG).   

• Expertise with Azure AI, vector stores, prompt/response evaluation, and performance optimization for LLM workloads.  

• Track record of shipping applied research to production and partnering with research teams on custom/finetuned models.  

• Familiarity with Responsible AI practices and inclusive design/accessibility standards.  
• Ability to influence across teams and drive ambiguous, multi-partner initiatives to outcomes.  
• Handson experiences taking LLM/ML features from prototype to production (evaluation, safety, telemetry, and iterative improvement).  

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. 

Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $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

Microsoft will accept applications for the role until October 17, 2025., Year.

#C+E #JoinCFP 

 Responsibilities: 

• Design and ship AI systems end-to-end—from exploration to production—spanning LLM based services, retrieval/grounding pipelines, and robust evaluation/observability.   

• Build agentic tools using workflows that reason across data and services, optimizing for safety, latency, and cost at cloud scale (Azure preferred).  

• Collaborate across research and product teams to adapt/finetune models (LLMs/SLMs, multimodal) for real customer scenarios.  

• Lead technical direction across features and services; mentor engineers; champion high engineering standards, reliability, and accessible, inclusive experiences.  

• Uphold Responsible AI, secure and compliance practices in design, data handling, and experimentation.  

• Participate in on call/operational excellence as part of a healthy, sustainable engineering culture; lead by example.