Software Engineer

Microsoft•Redmond, WA

4d•$102,100 - $219,200

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.

Requirements

Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Nice To Haves

Experience with distributed systems, micro-service architecture, scalability patterns, and high-availability architectures.
Experience contributing to solution design by exploring design options, documenting technical decisions, and proactively managing upstream and downstream dependencies while partnering with other teams to deliver scalable, reliable, and secure solutions.
Experience with REST Based API’s development, messaging patterns (e.g. Service bus, Event Hub, Storage Queues) and cloud storage technologies ( e.g. Cosmos DB)
Experience in deploying, monitoring, and operating services in the cloud.
Industry experience with cloud technologies (Azure, AWS, Google).
Familiarity with modern engineering practices such as CI/CD and version control systems like Git.
Experience leveraging AI-assisted development tools (e.g., GitHub Copilot, LLM-based coding assistants) to improve engineering productivity, code quality, and software delivery.
Problem-solving skills, with a data-driven approach to debugging and performance optimization.
Communication and collaboration skills.
Problem-solving, troubleshooting, and organizational skills.
Experience with or exposure to Agile and iterative development processes.

Responsibilities

Uses AI tools effectively across the SDLC, taking accountability for reviewing and validating AI‑generated outputs with minimal guidance.
Develops, reviews, and improves code with a focus on quality, security, and maintainability, while leveraging testing, telemetry, and best practices to prevent and resolve issues.
Collaborates on architecture and design decisions, evaluates options, and contributes to scalable, secure, and well‑documented solutions aligned with product requirements.
Applies best practices across security, compliance, performance, and automation, while continuously improving tools, processes, and system reliability at scale.
Executes project and release plans, breaking down work, ensuring secure and compliant deployments, and using safe rollout strategies like flighting and experimentation.
Maintains live‑site health through monitoring, incident response, and telemetry, improving troubleshooting processes and ensuring secure, reliable service operations.
Works with stakeholders to understand customer needs and incorporates both explicit and implicit feedback into feature design and continuous improvements.