Senior Software Engineer

Microsoft•Redmond, WA

3d•$119,800 - $234,700

About The Position

Commercial Engineering & AI (CEAI) partners closely with stakeholders to accelerate the transformation of Microsoft’s commercial business into a frontier organization. We bring together AI‑native engineering, modern platforms, and deep commercial insight to reimagine how work gets done at scale and with impact. Our mission is to unlock new ways of operating through intelligent systems while creating the conditions for our teams to do the most meaningful work of their careers. If you’re excited to build, experiment, and shape the future of commercial execution with AI at the core, we invite you to apply. Within this context, the Support Experience Group (SXG) organization is at the forefront of transforming Microsoft’s support ecosystem through AI-first innovation. Our mission is to build intelligent, scalable platforms that power partner and customer success, accelerating Microsoft’s commercial growth through modern, AI-driven experiences. As a Senior Software Engineer, you will design and ship core components of the Agentic support platform that Microsoft support relies on daily. You own features end to end, from prototype to production, working across orchestration, grounding, evals, observability, and the Software Development Kit (SDK) surfaces other engineers build on. You take real ownership of what you ship, help raise the bar for how agents are built and evaluated on the team, and grow your influence as you go. This role is for an engineer with a proactive approach who will be responsible for designing, operating, and evolving AI‑driven, end‑to‑end autonomous support workflows that are foundational to Microsoft’s next‑generation Support experience. The role sits at the intersection of AI engineering, live‑site operations, compliance, and business transformation, ensuring that AI‑managed support systems are production‑ready, trustworthy, and scalable.

Requirements

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
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

Nice To Haves

Experience building Large Language Model (LLM) -powered applications, Retrieval-Augmented Generation (RAG) pipelines, prompt engineering, agent frameworks (Semantic Kernel, LangChain), or fine-tuning with an eye for evaluation, latency, and cost
Proficiency in AI-native development working within Agent Harnesses ( GitHub Copilot Command-Line Interface (CLI) , Coding Agents), authoring Markdown specs/ Architecture Decision Records (ADRs) and YAML configs as Agent-consumable inputs, orchestrating multi-step Agentic workflows across the Software Development Life Cycle (SDLC), and reviewing Agent-generated code and Pull Requests (PRs) with production-grade rigor
Experience with shipping enterprise scale services
Experience shipping agent-based systems in production, including hands-on experience with evals, observability, and debugging
Experience standing up evals or observability for non-deterministic systems
Experience contributing to the safety posture of AI systems, including prompt-injection defences and audit trails
Experience owning and shipping significant features or architectural components end to end

Responsibilities

Build agentic workflows using frameworks like Azure AI foundry, Microsoft Copilot studio or equivalent.
Owning the run‑state reliability of AI‑driven support workflows, including incident response, live‑site health, and continuous tuning.
Adapting AI workflows to changing support business policies and operational processes (e.g., Service Level Agreement (SLA) calculations, case ownership, escalation models).
Driving customer trust, satisfaction, and sentiment, ensuring AI agents correctly understand intent and guide customers to resolution without degrading experience.
Ensuring security, privacy, and responsible AI compliance, including rethinking Role-Based Access Control (RBAC), data access, case ownership vs. processing, and data exposure.
Defining and implementing observability, monitoring, and intervention mechanisms for multiple AI agents operating concurrently.
Partnering across engineering, support business, compliance, and platform teams to establish scalable patterns for AI‑managed support.
Contributing to the vision and delivery of a platform that enables citizen developers to safely build AI agents for support workflows with reduced barrier to entry.
Collaboration across teams: you can align with partners and move work forward together