Principal Software Engineer

• Architecture Strategy & Roadmap (Cloud + AI + Agentic)
• Own the reference architecture and technical roadmap for AI/Agentic platform capabilities (e.g., orchestration, skills, tools/plugins, memory, retrieval, evaluation, observability, governance)
• Translate Customer Success business objectives into platform investments and architectural decisions, balancing speed-to-value with security, compliance, cost, and long-term maintainability
• Establish clear architectural guardrails and decision frameworks (e.g., “build vs. buy,” “Copilot Studio vs. Foundry,” “RAG vs. fine-tune,” “central vs. federated patterns”)
• Technical Leadership & Architectural Governance
• Lead architecture/design reviews for major initiatives
• drive alignment on system boundaries, contracts, dependency management, and resiliency
• Define and standardize architecture patterns (multi-tenant SaaS, event-driven architectures, secure data access, model routing, agent safety controls)
• Create reusable templates, “golden paths,” and reference implementations to accelerate engineering delivery across teams and reduce fragmentation
• Responsible AI, Security, Privacy, and Compliance by Design
• Embed Responsible AI principles into agentic solution design (human-in-the-loop, safety mitigations, evaluation, transparency, and auditability)
• Partner with security and compliance stakeholders to ensure services meet required controls and operational standards, and to drive alignment between policy intent and implementation
• Define secure patterns for prompt/data handling, secrets management, identity, and access governance for AI systems
• Platform Reliability, Operability & Cost Management
• Drive architecture that improves reliability, observability, incident response readiness, and cost efficiency across AI-enabled services
• Establish telemetry standards (quality, safety, latency, cost, success metrics) and ensure teams instrument consistently to enable operational excellence at scale
• Design for production: rollout/rollback strategies, evaluation gates, and operational playbooks for AI/agent releases
• Cross-Org Influence & Coalition Building
• Build coalitions across broader Microsoft engineering/product groups to deliver complex, large-scale initiatives
• resolve long-standing misalignments
• and hold stakeholders accountable for commitments
• Act as a trusted technical advisor to senior stakeholders, creating clarity, driving alignment, and enabling execution across multiple teams and disciplines
• Mentorship, Technical Community, and Talent Scaling
• Mentor engineers
• enhance architecture quality, engineering discipline, and Responsible AI rigor
• Contribute to internal technical communities through documentation, brown bags, and reusable engineering guidance—amplifying impact through others.

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.

• Master’s degree in computer science, Engineering 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
• 10+ experience in software engineering or solution architecture, with demonstrable success building and operating complex systems
• 10 + years of full-stack development across frontend, backend, and cloud infrastructure, with a proficient command of data engineering, AI/ML systems, and deployment architectures
• Proficient coding skills in C#, Python, JavaScript, and React
• Experience designing and shipping AI/ML GenAI solutions, including one or more of: Retrieval-Augmented Generation (RAG), enterprise search, vector retrieval
• LLM orchestration and agentic workflows
• AI evaluation/monitoring, safety and quality measurement
• Experience architecting and delivering cloud-native, distributed systems at scale (multi-service systems, reliability, performance, and operability)
• Proficient engineering fundamentals and ability to work “hands-on when needed” (prototyping/reference implementations, architectural spike investigations, debugging complex issues)
• Experience with cross-team influence - driving alignment and execution across multiple disciplines and stakeholders
• Experience communicating clearly with technical and non-technical audiences
• comfort presenting senior leadership.