Principal Software Engineer

Microsoft • Redmond, WA

11d • $142,800 - $304,200

About The Position

Joining Microsoft’s C+AI organization means contributing to the end-to-end AI stack powering Azure’s innovation. As part of the FIT training team, the Principal Software Engineer develops AI infrastructure and scientific methods that accelerate the creation and training of agentic AI systems. The work supports LLMs, SLMs, multimodal and code-specific models, using proprietary and open-source frameworks to deliver reliable, enterprise-grade agentic workflows.

The role calls for an independent, adaptable problem-solver who can lead by example, write efficient code, debug complex training jobs, document findings, and continuously improve. The team values an agile, startup-style approach: iterating quickly, adapting to changing priorities, and collaborating in a fast-paced environment. The position also contributes to Microsoft’s inclusive culture and mission to empower people and organizations.

Requirements

• Bachelor’s degree in Computer Science or a related technical field and 6+ years of technical engineering experience coding in languages including C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
• Strong coding skills in one or more systems or backend languages such as Python, Go, Rust, C++, C#, or Java.
• Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.
• Curiosity, independence, adaptability, problem-solving ability, and motivation to learn and create meaningful impact.
• Ability to lead by example, write efficient code, debug complex training jobs, document findings, and pursue continuous improvement.
• Ability to collaborate effectively in fast-paced, dynamic environments and adapt to changing priorities.

Nice To Haves

• Master’s degree in Computer Science or a related technical field and 8+ years of technical engineering experience coding in languages including C, C++, C#, Java, JavaScript, or Python; or a bachelor’s degree in the same fields and 12+ years of such experience; or equivalent experience.
• 5+ years of software engineering experience with significant ownership of production services, cloud platforms, distributed systems, or developer infrastructure.
• Strong experience building and operating containerized platforms using Kubernetes or similar orchestration systems.
• Experience designing reliable production APIs, backend services, or control-plane systems that manage compute, storage, networking, or runtime environments.
• Solid understanding of cloud infrastructure fundamentals, including identity, networking, storage, observability, capacity planning, security, and safe deployment practices.
• Experience diagnosing production issues using logs, metrics, traces, dashboards, and incident response processes.
• Demonstrated ability to lead technical design and retrospective efforts, drive ambiguous projects to completion, mentor engineers, and collaborate across teams.
• Experience with Microsoft Azure, AWS, or Google Cloud, especially managed Kubernetes, container registries, object storage, private networking, identity, secrets, and monitoring services.
• Experience building multi-tenant platforms where reliability, fairness, quota management, isolation, and security are important.
• Experience with sandboxed execution environments, remote development environments, hosted notebook or tool environments, evaluation infrastructure, or ephemeral compute platforms.
• Experience with container image build systems, registry authentication, image caching, package caching, artifact distribution, or startup-latency optimization.
• Experience with cloud networking concepts such as ingress, DNS, proxies, egress control, private endpoints, service routing, and traffic management.
• Experience with secure runtime design, including authentication, authorization, workload identity, secret handling, network isolation, and protecting shared infrastructure from untrusted workloads.
• Experience with AI infrastructure, agent execution, evaluation platforms, GPU workloads, Windows or Linux runtime environments, or VM/container hybrid systems.
• Experience improving service operability through structured logging, distributed tracing, dashboards, alerting, automated validation, and incident playbooks.

Responsibilities

• Collaborate with engineers and researchers to build and optimize training infrastructure and tools for LLMs, SLMs, multimodal models, and code-specific models.
• Design, build, and improve highly scalable and reliable services.
• Design and implement services that serve production traffic and fulfill security and privacy requirements.
• Help deliver and improve engineering systems and practices that ensure service quality in complex cloud environments.
• Contribute to deploying and monitoring services in production environments.
• Lead technical design and retrospective efforts, drive ambiguous projects to completion, and mentor other engineers.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior