Software Engineer, Agents

Mercor · New York, NY · 2 wk ago

On-siteEngineering$130k–$500k/yrFull-time

We're looking for a strong engineer who can build agentic products that scale. You will work with:

You’ll be team-matched to where you can have the most impact, on one of the following:

Automation – 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.
Studio – Own Mercor’s evaluation system & annotation platform for RL environments and tasks. Build harnesses, agents, verifiers, and the end-to-end infrastructure for producing frontier data. Work closely with researchers at frontier AI labs to jointly shape the direction of next-generation models.

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.

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.

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