Principal Software Engineer

Microsoft•Redmond, WA

About The Position

The Commerce Financial Platform organization 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. Join us if you're passionate about redefining how people engage with AI at enterprise scale, optimizing processes, and building innovative products that make a difference.

Requirements

8+ years building and shipping production software/services including 3+ years with modern ML (e.g., transformer‑based LLMs) and applied AI/ML systems.
Coding skills in one or more: Python, C#, or C++—with design/architecture experience for cloud services (Azure preferred).
Hands‑on experience taking LLM/ML features from prototype to production (evaluation, safety, telemetry, and iterative improvement).
Ability to influence across teams and drive ambiguous, multi‑partner initiatives to outcomes.
Bachelor’s degree in computer science/engineering or equivalent practical experience.
Ability to meet Microsoft, customer, and/or government security screening requirements, including the Microsoft Cloud Background Check (on hire/transfer and periodically thereafter).

Nice To Haves

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/fine‑tuned models.
Familiarity with Responsible AI practices and inclusive design/accessibility standards.

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 and tool‑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/fine‑tune 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.