Software Engineering

About the role

Be a problem solver: seek out meaningful customer and operational problems, challenge assumptions, and focus engineering effort on outcomes rather than predefined solutions.

Partner with cross-functional teams - including product and program management, datacenter operations, supply-chain stakeholders, and partner engineering teams - to observe workflows, gather evidence, uncover root causes, and define the right problems to solve.

Own problems end to end, from discovery and problem framing through technical design, implementation, validation, production rollout, and measurement of customer and business impact. Use an AI-native engineering approach in day-to-day work.

Apply coding agents, generative AI, automation, and emerging engineering tools to accelerate exploration, implementation, testing, review, documentation, and operations while maintaining appropriate human judgment and accountability.

Identify opportunities to embed AI, agents, and automation into datacenter inventory workflows and shared engineering capabilities; validate their value through rapid experiments and measurable results. Design and build production-grade inventory services, APIs, workflows, and user experiences across asset lifecycle, inventory, component tracking, movement, fulfillment, break-fix, and decommissioning scenarios.

Translate ambiguous business and operational needs into clear technical plans, interfaces, data contracts, and maintainable implementation patterns. Make engineering tradeoffs across reliability, security, usability, performance, cost, and delivery speed, and communicate those decisions clearly to technical and non-technical partners.

Own the quality and production readiness of delivered capabilities, including automated testing, observability, secure data handling, safe deployment, incident response, and continuous improvement. Use telemetry, customer feedback, operational data, and experiments to evaluate solutions, diagnose issues, and determine whether to scale, redirect, or stop an approach.

Contribute to design and code reviews, share knowledge, and help the team adopt effective AI-native and software-engineering practices through working software and practical guidance. Bachelor's Degree in Computer Science or related technical field AND 2+ years of technical engineering experience coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python; OR equivalent experience.

Bachelor's Degree in Computer Science or related technical field AND 4+ years of technical engineering experience; OR Master's Degree in Computer Science or related technical field AND 2+ years of technical engineering experience; OR equivalent experience. Experience designing and delivering production software, developer tools, services, or platform components as part of a collaborative engineering team.

Experience using generative AI models, coding agents, or engineering platforms to build software, with awareness of evaluation, reliability, security, and appropriate human oversight. Experience improving developer workflows, engineering systems, operating practices, or developer experience and using feedback or measurements to assess the results.

Working knowledge in one or more areas such as cloud platforms, distributed systems, developer tooling, identity and security, observability, CI/CD, testing infrastructure, or safe deployment. Experience building or operating products for developers, AI-enabled engineering workflows, internal developer platforms, developer tooling, or cloud infrastructure is preferred.

Demonstrated ability to work through moderately ambiguous problems, make sound implementation tradeoffs, and take well-defined features from design through production operation. Demonstrated ability to communicate technical ideas clearly, collaborate across team boundaries, learn from feedback, and contribute positively to team engineering practices.

These requirements include, but are not limited to the following specialized security screenings: