About the role:

Foundation AI builds the platforms, services, and infrastructure that enable machine learning and generative AI across Roblox. As a Principal Engineer on this team, you'll set technical strategy and direction across areas such as model training and inference, LLM services, agent infrastructure, data systems, experimentation, evaluation, and developer tooling. You'll be accountable for the architecture and long-term health of systems that many teams depend on, and you'll shape how Roblox builds AI — partnering with engineering, product, research, data, infrastructure, safety, creator, engine, discovery, and economy. You will report to an Engineering Manager within the Foundation AI organization.

You will:

• Define the multi-year technical vision and architecture for platforms and services that power machine learning, generative AI, and agentic experiences across Roblox.
• Drive the hardest, most ambiguous, highest-leverage problems on the platform from framing through production on multi-provider inference resiliency and scaling information retrieval infrastructure for agentic use and be accountable for the outcomes.
• Establish the standards, paved paths, and guardrails that make the platform self-serve for every team at Roblox — multi-tenant usage attribution and metering, built-in spend controls, and fast, ticket-free onboarding.
• Make foundational trade-offs in quality, latency, reliability, cost, and responsible data use for systems operating at Roblox scale — treating instrumentation and observability as a first principle of the architecture, not an afterthought.
• Own the operational standard for the platform at scale — SLOs, capacity planning, on-call, and incident response and design for graceful degradation and fast recovery, not just steady-state correctness.
• Identify high-impact opportunities and risks ahead, and build alignment across engineering and leadership to act on them.
• Multiply the impact of other engineers through technical mentorship, design and code review, and setting the bar for engineering excellence.

You have:

• An undergraduate/graduate degree in computer science, a related technical field, or equivalent practical experience.
• 8+ years of experience building and operating large-scale production software, distributed systems, cloud services, or related infrastructure.
• A sustained track record of designing and owning foundational systems or platforms with organization- or company-wide impact.
• Deep expertise in one or more of machine learning, generative AI, distributed systems, data infrastructure, or developer platforms, with the breadth to reason across all of them.
• Expert proficiency in one or more of Go, Python, or Rust, and the judgment to choose the right tools for durable systems.
• A history of setting technical direction across multiple teams and driving large, cross-organizational efforts to completion.
• Exceptional communication and influence skills, with the ability to align engineers, product, and leadership around a technical strategy.

Nice to have:

• Experience building or operating an LLM gateway, inference-serving, or model-routing layer — multi-provider failover, rate limiting, and token/cost accounting at scale.
• Hands-on work with vector databases, similarity search, or knowledge graphs, and with RAG or agentic systems (retrieval pipelines, agent memory, context management, evaluating non-deterministic systems).
• Experience designing multi-tenant platforms — usage attribution, metering, spend controls, and self-serve onboarding.
• Background in GPU infrastructure or ML inference efficiency (batching, quantization, accelerator utilization, cost optimization).