The platforms in our Engineering Acceleration org dictate how thousands of Roblox engineers ship, and how every backend service gets built, deployed, and kept reliable at scale. They sit on the critical path for production reliability, developer velocity, and security posture. Reporting to Andrew Swerdlow, you will rethink the entire engineering toolchain from the ground up to be agentic-native, creating a world where AI agents are first-class participants in software development and humans set direction and supervise. This is a unique opportunity to define what modern engineering infrastructure looks like at one of the largest platforms in the world.
You will:- Reimagine the engineering toolchain as agentic-native, designing the platforms, guardrails, and feedback loops that let AI agents safely drive migrations, validation, and routine operational work.
- Set a bold technical direction for AI-driven quality, including agent-generated tests, automated coverage of untested paths, intelligent verification, and continuous-deployment workflows.
- Make software quality and SEV prevention a measurable property of the platform by investing in safe-change mechanisms, automated verification, progressive rollout, and fast, reliable rollback.
- Drive down operational toil through automation, transforming manual, repeat work like patching and large-scale migrations into self-serve or agent-driven workflows.
- Own and drive the roadmap, aligning cross-pod plans and execution against company goals for safe rollouts.
You have:- Experience leading and growing engineering teams (including managing managers and/or senior ICs), with a strong people-development track record.
- Strong technical depth in backend/distributed systems and cloud infrastructure, enabling you to engage credibly on system design and technical decisions.
- A track record delivering internal developer platforms, CI/CD, or deployment systems at scale for many internal customers and services.
- A strong point of view on how AI/agentic tooling changes engineering workflows, coupled with hands-on familiarity with the modern AI engineering stack, AI coding tools, eval design, and open-weight models.
- Demonstrated cross-organizational collaboration and excellent communication skills, with the ability to translate ambiguous, multi-system problems into concrete, executable plans.
- (Preferred) Backend proficiency in C# and/or Go, and familiarity with Kubernetes/Nomad (Hashistack), Temporal, and AWS.
- (Preferred) Hands-on experience applying AI/agents to engineering workflows, with a background in safe/staged rollouts (canary, feature flags) and incident prevention/automated verification.
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.
Annual Salary Range
$399,420-$457,970 USD
Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).
