- Location
- San Mateo, CA, United States · San Mateo, CA
- Workplace
- Hybrid
- Department
- Engineering
- Seniority
- Lead
- Experience
- 8+ years
- Visa
- Not sponsored
Description
Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.
At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.
A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.
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).
For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page.
Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).
Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.
For US based roles only, please note the Company may not be able to employ candidates for this role who have United States work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time.