Software Engineer, Agents
Listed by employer · Checked
Older posting · still listed ·
- Work arrangement
- onsite
- Employment
- FullTime
- Stated compensation
- USD 160,000–500,000 1 YEAR
Does the location policy fit?
Choose where you would work from. We’ll compare it with the posting’s stated requirements.
Choose a country to check geographic compatibility. The source requirements are available below.
The employer’s posting date is more than 60 days ago. It remained listed at our last successful check; it may be a long-running or evergreen opening. Confirm availability on the original posting before applying.
Browse jobs posted in the past 60 days →This checks the posting’s stated requirements, not your legal right to work. Confirm details with the employer.
Requirements
1 with evidence8 unclear or unstated- Remote policy
- onsite
“Provider workplace type: onsite”
From employer posting metadata - Employment type
- FullTime
- Compensation
- USD 160,000–500,000 1 YEAR
8 fields not stated in this posting
- Employer sponsorship
- Not specified
- Geographic scope
- Not specified
- Degree requirement
- Not specified
- Security clearance
- Not mentioned
- Timezone / hours
- Not specified
- Citizenship requirement
- Not mentioned
- Minimum experience (years)
- Not specified
- Work authorization
- Not specified
These details were not stated in the tracked posting. Confirm with the employer.
Original job description
Reading view uses normalized posting text so exact evidence excerpts can be highlighted.
Show less description
Original formatting and links
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
We're looking for a strong engineer who can build agentic products that scale. You will work with:
Backend: Python, FastAPI, Django, Pydantic
Frontend: Next.js, React, TypeScript, Tailwind
Data: PostgreSQL, MySQL, Snowflake, DuckDB, Redis
Orchestration/Infra: Kubernetes, Temporal, Modal, Woz
Agents/LLM: LangGraph, LangChain, FastMCP, Harbor, NemoGym
Observability: Datadog, PostHog, LangSmith
At the end of the process, you’ll be team-matched to where you can have the most impact, on one of the following:
Automation – We build intelligent systems and agents that automate operational work at scale—handling talent management, decision-making insights, and knowledge access—so humans can focus on higher-level thinking.This is a newly formed, CEO-facing team focused on 0→1 product development, with a strong emphasis on business impact. The work is highly cross-functional, touching nearly every system across the company.
Studio – We own Mercor’s evaluation system & annotation platform for RL environments and tasks. We build harnesses, agents, verifiers, and the end-to-end infrastructure for producing frontier data. Our mission is to scale up high quality RL environments/tasks and expand their capabilities. We work closely with researchers at frontier AI labs to jointly shape the direction of next-generation models.
What You’ll Do
Own agentic features end-to-end — from scoping with researchers/ops partners through implementation, launch, and iteration on real customer feedback.
Design and ship LLM agents, harnesses, and verifiers — including the tools, prompts, and policies that make them reliable.
Build the Python/FastAPI services and Temporal/Modal pipelines that orchestrate agent runs, human-in-the-loop review and iterations.
Build state of the art RL environments that expand the capabilities of frontier agents, with realistic enterprise apps, simulated coworkers, and rich company data rooms that support tasks spanning hours to days.
Build tooling that turns agent trajectories into insight, from statistical analysis to automated failure mode detection.
Build and refine the full-stack surfaces and data infrastructure — craft Next.js/React interfaces where operators and experts work with agents, evolve data models to give agents the structured context and audit trails they need.
Define agent quality and drive continuous improvement — build evals, instrument traces, analyze failure modes, and iterate on prompts, tools, and guardrails while raising the bar for reliability, cost, latency, and UX.
Partner cross-functionally to shape agent autonomy — work with Product, Design, Research and Ops to draw the lines between autonomous action, propose-and-approve flows, and human-in-the-loop decisions.
Why Mercor
Impact: Your work powers how the world’s leading AI labs train and test their models.
Learning: Get early insights into frontier model capabilities months before the market.
Growth: Work on both infrastructure and research-adjacent projects with fast paths to ownership.
Benefits
Bi-annual performance bonus structure
Generous equity grant vested over 4 years
Up to $15k Relocation bonus
$10K housing bonus (if you live within 0.5 miles of our office)
$1.5K monthly stipend for meals
Free Equinox membership
$200 monthly laundry reimbursement
$200 monthly personal wellness reimbursement
Health, Dental, Vision insurance
Matched by role category. Review each posting’s requirements before applying.
