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Based in Redmond, this principal individual contributor role will help define and deliver an end-to-end strategy across Retrieval, Context Engineering, WorkIQ/FabricIQ, and potentially Knowledge Graphs to drive a winning E2E approach for Microsoft. In addition to helping define the overall technical strategy and roadmap with partner PMs and engineering leaders, you will be hands-on building and integrating services step-by-step, writing production code across the product.
Job Responsibility:
Drive end-to-end technical strategy and roadmap across Retrieval, Context Engineering, WorkIQ/FabricIQ, and Knowledge Graph.
Design and implement scalable cloud services and platform components
write production code to deliver features and integrations.
Partner closely with PMs and engineering leads to define an ambitious but achievable execution plan.
Collaborate with multiple engineering ICs to build, integrate, and ship E2E scenarios across teams.
Establish engineering best practices for reliability, security, performance, and operational excellence in Azure.
Aggressively introduce and scale AI-assisted coding practices by pairing with developers and helping implement features using these workflows.
Requirements:
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, Python or equivalent experience.
Proven experience as a senior IC software engineer building and operating cloud services (Azure preferred).
Expertise building retrieval systems, context engineering, and/or knowledge graph systems.
Experience with distributed systems, service reliability, observability, performance, and live-site operations.
Experience leading technical direction across multiple partner teams and delivering cross-team integrations.
Ability to translate ambiguous problem spaces into concrete technical roadmaps and executable plans.
Familiarity with LLM application patterns (RAG, agents/tools), data pipelines, and evaluation/quality loops.
Demonstrated success driving adoption of AI-assisted coding practices and developer productivity workflows.
Experience with multi-tenant platform design, security/compliance considerations, and large-scale integration testing.