MercorMember of Technical Staff, Mercor Enterprise Platform
Mercor is hiring a Member of Technical Staff, Mercor Enterprise Platform in San Francisco, United States. It pays $160k-$500k a year and Level rates it ; you can apply on Mercor.
Level's read on this job
- Builds AI ●●●● is how Level rates this role: the job is building AI systems.
- The posting mentions Go, TypeScript and Postgres among its tools and skills.
- Level classes it as a mid-level role.
- Mercor has 88 other open roles on Level.
AI in this role
Build and operate the enterprise agent platform and infrastructure powering AI workflows at Mercor.
Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.
Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.
About the Role
The Mercor Enterprise Platform is what enterprise customers and our Applied AI engineers use to build and run complex agents. It is both deployed into customer environments and hosted by us. It is also the central platform for every internal agent at Mercor, scaling to several thousand agent runs per day, and still growing.
You will work across the full stack: enterprise-grade security and the routing plane, isolated execution, and the intelligence plane that turns production runs into improvements. This is a pure platform and infrastructure engineering role, though you will work closely with the Applied AI engineers embedded with our customers. The quality of this platform bounds what the business can sell.
Nobody has settled how agent platforms should be built, and this is one of the few places that question is being answered in production, with economically viable agents as the bar.
Tech we use: Go, TypeScript, Postgres, Kubernetes, Harbor, and Terraform.
Read more about how we think about this: The Three Planes of Enterprise Agent Systems
Responsibilities
Design, build, and operate the services the platform is made of: authn and authz, credential brokering, routing, sandboxing, and orchestration.
Design the interfaces other engineers build agents against, and keep the paved path the easiest one to follow.
Build the event-driven backbone so that ingestion stays idempotent when services scale horizontally.
Own the deployment model itself, from our hosted offering to customer VPCs and multi-cloud, so a new deployment needs no bespoke build.
Keep tenants isolated by construction, so one run cannot reach or spend beyond its own quota.
Own latency, throughput, and cost per run as volume grows, along with the production debugging that comes with them.
Set the direction for the parts of the platform you own, not just the implementation.
Partner closely with Applied AI engineers on the hardest problems coming out of deployments. They own the customer relationship, you own the platform.
What We're Looking For
Bachelor’s Degree in Computer Science or a related technical degree such as Electrical Engineering, Physics, Mathematics, Computer Engineering, Information Systems or Statistics
5+ years of experience building high scale, complex software systems
You have built and operated a platform other engineers depended on, and owned the architectural calls on it rather than only the implementation.
Hands-on with several of these primitives: authn and authz, secrets, isolation, orchestration, egress, and durable state, in more than one cloud.
A drive to keep making systems faster and cheaper after they already work.
Demonstrated ability to work independently on ambiguous, loosely specified problems.
Bonus: experience with LLM applications, agent frameworks or harnesses, evals, or deployed software.
Why Mercor
Impact: Every agent Mercor runs for an enterprise customer runs on the platform you build.
Learning: Depth in agent infrastructure, and the isolation problems that come with running other people's code.
Growth: Deep ownership of platform surface area, with fast paths to owning more of it.
Benefits
Up to $15k relocation bonus
$10K housing bonus (if you live within 0.5 miles of our office)
$1.5K monthly stipend for meals
Generous equity grant vested over 4 years
Free Equinox membership
$200 monthly laundry reimbursement
$200 monthly personal wellness reimbursement
Health, Dental, Vision insurance
How we rate this
Member of Technical Staff, Mercor Enterprise Platform at Mercor rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where platform engineering was part of your work. What did you do?
- Tell me about a project where infrastructure was part of your work. What did you do?
- Tell me about a project where agent systems was part of your work. What did you do?
- Tell me about a project where orchestration was part of your work. What did you do?
- Tell me about a project where sandboxing was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Platform Engineering, Infrastructure, Agent Systems, Orchestration, and Sandboxing. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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