Engineering Manager, Platform Systems

What you'll do

• Define and own the long-term technical strategy for Platform Systems including reliability, scalability, and cost efficiency.
• Translate technical strategy into an actionable engineering roadmap for the team and the broader organization.
• Own the subsystems for observability, evaluation, and tooling required for next-generation ML architecture.
• Establish engineering excellence standards for observability, reliability practices, and on-call hygiene.
• Hire, develop, and retain a high-performing team of engineers across various seniority levels.
• Guide the AI stack modernization effort by establishing migration paths and aligning with partner teams.
• Partner with director-level leadership to represent Platform Systems in strategic planning and investment advocacy.
• Improve developer productivity by removing friction, automating toil, and investing in internal tools.

What we're looking for

• Significant experience leading platform or infrastructure engineering organizations operating distributed systems at scale.
• Strong technical depth in distributed systems architecture, tradeoffs, and design decisions.
• Hands-on experience building subsystems for advanced agentic architectures, including memory, trace, eval, and replay pipelines.
• Experience with ML infrastructure at scale, including online and offline model training pipelines.
• Track record of building high-performing engineering teams and developing senior technical talent.
• Track record of improving system reliability, reducing infrastructure costs, and accelerating engineering velocity at scale.
• Experience developing reliable, scalable machine learning platforms for recommendation, ranking, or personalization systems (preferred).
• Working knowledge of generative AI alongside traditional machine learning approaches (preferred).