Six Figure Work

Principal Software Engineer, Agent Infrastructure

Roblox

Company websiteroblox.com (Roblox, opens in new tab)

Base salary $278,530  to $345,040

Employer-published annual base salary, USD. Advertised base range in San Mateo, CA

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  • LocationSan Mateo, CA
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (1 h ago) · observed since

About this job

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.

Why Roblox & Agent Infra

The Agent Infra team builds the infrastructure that runs autonomous AI agents at Roblox for millions of creators building experiences on our platform, and for thousands of Roblox engineers shipping production code every day.

Agent workloads break the assumptions most infrastructure is built on. They run for hours instead of milliseconds, they’re non-deterministic, they execute code nobody wrote, and they need real credentials against real systems to be useful at all. Making that safe, durable, and cost-effective at Roblox’s scale is the hard problem our team is solving.

As an early member of the Agent Infra team, you’ll work alongside an experienced engineering team on systems that are already in front of real users, at scale, in a field that didn’t exist two years ago.

You Are

  • Demonstrated experience: 8+ years building and operating backend, distributed, or infrastructure systems in production, including systems you designed that held up at scale for years.
  • Deep expertise in at least one of our core domains: workflow orchestration, scalable backend infrastructure, agentic runtimes, or secure sandboxing and access.
  • Hands-on: You spend most of your time building, and you write production code in Go, Python, Rust, or similar.
  • Agent-native: Agents drive your daily work. You’ve experimented with swarms, loops, and orchestration, you have strong opinions on harness and model choice, and you’re constantly evolving your agentic workflow.
  • Experienced with agents in production: You’ve run agents against real systems, seen how they fail, and know what the infrastructure underneath should do about it.
  • Bachelor’s degree or equivalent experience in Computer Science, Computer Engineering, or a similar technical field.

You Will

  • Set the technical direction: Own the design and implementation of Roblox’s core agent infrastructure, and scale it to serve every internal and external customer.
  • Drive reliability and security: Keep long-running agents alive through deploys, restarts, and outages. Run untrusted code in sandboxes that keep credentials out of the agent’s reach and control what it can reach on the network. Define the SLOs and observability that hold the platform to account.
  • Raise the bar: Keep learning and experimenting with agentic workflows, and bring what works to the team and the wider Foundation AI org.
  • Align across the org: Partner with Security, Engineering Efficiency, and Infrastructure so the agent platform and the systems it depends on are built in the same direction.
  • Multiply the team: Mentor senior engineers, lead design reviews, and push how far agents can build the agent platform itself.

Nice to Have

  • Security experience with systems that run untrusted code: sandbox and container isolation (gVisor, Firecracker, microVMs), Kubernetes hardening, network segmentation and egress control.
  • Experience working with Temporal, AWS, and self-hosted models.
  • Experience building and deploying production systems on Kubernetes, using GitOps and Argo CD.
  • Contributions to open source or experience building your own product with real user traction.

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

$278,530—$345,040 USD

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.

Source: Roblox on Greenhouse · View original posting (opens in new tab)

Pay in context

This role's base floor ($278,530) is above 88% of the 1,514 Data & ML roles in California listed on this site; 1 other lists the same floor. Their median floor is $187,500; the middle half runs from $159,200 to $229,375.

Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 7, 2026.

This range next to 6 other live Roblox roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live Roblox roles with the nearest advertised base floor
RolePublished base
Principal Software Engineer, Agent Infrastructure (this listing)$278,530 - $345,040
Senior Product Manager, AI Compute Infrastructure$280,540 - $330,950
Senior Product Manager, App Performance & Architecture$280,540 - $330,950
Senior Product Manager, UGC Marketplace$280,540 - $330,950
Senior Product Manager, Engineering Acceleration$280,540 - $330,950
Senior/Principal Product Manager, Engine Networking$280,540 - $330,950
Principal/Senior Machine Learning Scientist - Search and Discovery$278,530 - $345,040

Same $100K to $400K scale as every card. All Roblox roles · How to read the bar

Observed changes

  1. Began meeting the published-salary criteria
  2. First observed on the employer's board
Observed since
Employer-stated posting date
2026-10-13
Where this pay comes from

Location as the employer wrote it: San Mateo, CA, United States

$278,530—$345,040 USD

Method
Employer text, read with fixed rules and re-verified
Checked
Rule set
us-base-v2

The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.