Software Engineer, Applied AI - Environments Platform

Mercor; San Francisco (CA); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Performance bonus

Equity grant

Relocation bonus

Housing bonus

Meals stipend

Equinox membership

Laundry reimbursement

Wellness reimbursement

Health insurance

Job summary

Mercor seeks an experienced backend/infrastructure engineer to own the environments platform, from authoring to lab delivery. You will design and operate the core runtime, build APIs and services for lab customers, and ensure reliability at scale across thousands of sandboxes.

You will work with product, operations, and research to translate ambiguous requirements into robust, scalable systems, with ownership of end-to-end delivery and on-call responsibilities.

Qualifications

• 3+ years building and operating production backend or infrastructure systems.
• Hands-on API design with versioning and backward compatibility.
• Relational databases: data modeling, query performance, safe migrations.
• Advanced Linux and container proficiency; debugging at scale.
• Experience running workloads on Kubernetes or serverless like Modal.
• Production services: containers, CI/CD, monitoring, alerting under real traffic.
• Clear written and verbal communication; strong ownership and shipping bias.

Responsibilities

• Own pipelines taking an environment from authoring to lab handoff, including packaging, validation, and versioning.
• Design, build, and operate the core environment runtime for scalable sandbox execution.
• Build services other teams use to run environments and the APIs their lab customers depend on.
• Extend harnesses to run agents inside environments and ensure results align with stack outputs.
• Own features end to end: scope, design, ship, instrument, and keep healthy in production.
• Work with modern tools, libraries, and frameworks to stay current.
• Build for scale and reliability in pipelines and job systems: queueing, batching, retries, backpressure, recovery.
• Participate in on-call for owned systems and document learnings (RCCA).
• Collaborate with product, operations, and research to turn ambiguous requirements into shippable systems.

Skills

Data structures

Concurrency

Distributed systems

API design

Relational databases

Linux

Containers

Kubernetes

Serverless (Modal)

Production systems

Tools

Modal

Temporal

Airflow

Dagster

CI/CD tooling

Terraform

Job description

About Mercor

Mercor's mission is to organize human intelligence for the AI economy. We build the infrastructure that enables frontier AI labs and enterprises to train, evaluate, and improve AI on real-world professional work. More than five million experts have joined our network, and we pay out over $5 million daily for their knowledge and expertise.

We built our training and evaluation infrastructure alongside the world's leading AI labs. Now, we're bringing those capabilities to enterprises across industries, enabling them to train, evaluate, and improve AI using their own expertise and standards. Our APEX benchmarks measure how AI performs on economically valuable work, while our enterprise evaluations and post-training capabilities turn those insights into measurable improvements across real-world workflows.

Our work sits at the intersection of frontier AI, human expertise, and real-world application. We're solving problems few companies have encountered, with the opportunity to influence what the world's most advanced AI systems become capable of doing. We're looking for people who bring different perspectives, take ownership, exercise sound judgment, and hold themselves to an exceptionally high standard. You'll have the opportunity to do consequential work alongside talented colleagues who challenge one another, collaborate openly, and share a commitment to excellence.

Mercor is profitable and recently raised a $750 million Series D at a $20 billion valuation. We work in person five days a week in San Francisco, New York, and London.

About the Role

Frontier labs train and evaluate their models inside environments Mercor builds: sandboxed codebases, enterprise applications, multi-tool agent worlds, and the verifiers that score what an agent did. The Environments Infrastructure team owns the platform that builds those environments, runs them at scale, and gets them to the customer, however a given customer wants to consume them, from a service they call directly to a dataset they run in their own stack.

That makes this team the layer between everything Mercor authors and everyone who runs it. We build the core environment runtime, the structure of the environments themselves, the services that other teams at Mercor build on, the integrations our lab customers build against, and the pipelines that carry an environment from authoring to a training run. Every environment Mercor ships goes through this stack.

The team is small, the surface area is large, and most of the big design questions are still open. You will own real pieces of this platform end to end and see what you build in use at the biggest AI labs within weeks of shipping.

What you will Do

• Own the pipelines that take an environment from authoring to a lab's hands, including the packaging, validation, and versioning that make a delivery trustworthy.
• Design, build, and operate the core environment runtime: how environments are built, isolated, launched, and torn down across tens of thousands of concurrent sandboxes.
• Build the services other teams at Mercor use to run environments, and the APIs and integrations our lab customers build against.
• Build and extend the harnesses that run agents inside our environments, and keep results consistent between our stack and a lab's.
• Own features end to end: scope the problem, write the design, ship it, instrument it, and keep it healthy in production.
• Work on modern cutting edge tools, libraries and frameworks.
• Build for scale and reliability in the pipelines and job systems that move work through the platform: queuing, batching, retries, backpressure, and recovery when things break.
• Participate in on-call for the systems you own and write up what you learn in RCCA.
• Work directly with product, operations, and research partners to turn ambiguous requirements into systems that ship.

What we are Looking For

• 3+ years building and operating production backend or infrastructure systems.
• Strong fundamentals: data structures, concurrency, distributed systems, and quality code contributions.
• Hands-on API design, with an understanding of versioning and backward compatibility.
• Solid relational database skills: data modeling, query performance, and safe migrations.
• Deep comfort with containers and Linux: image builds, isolation, networking, and debugging at scale.
• Experience running workloads on Kubernetes or a serverless container platform like Modal.
• Experience running services in production: containers, CI/CD, monitoring and alerting, and debugging issues under real traffic.
• Clear written and verbal communication. High ownership, pragmatism, and a bias toward shipping.

Nice to Have

• Experience with agent harnesses, RL environments, or evaluation infrastructure.
• Experience with workflow orchestration systems like Temporal, Airflow, or Dagster.
• Experience building or integrating with LLM-backed services in production (evaluation, orchestration, or serving).
• Familiarity with sandboxing and microVM runtimes such as gVisor, Firecracker, or Kata.
• Terraform or other infrastructure as code, and production experience on more than one cloud.

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

Mercor is an Equal Opportunity Employer and is committed to providing equal opportunity to all employees and applicants. Mercor does not discriminate based on actual or perceived race, color, creed, religion, national origin, ancestry, citizenship status, age, sex or gender (including pregnancy, childbirth, related medical conditions and lactation), gender identity or gender expression, sexual orientation, marital status, military service and veteran status, disability, protected medical condition as defined by California or local law, genetic information, or any other characteristic protected by applicable federal, California, or local laws and ordinances. Further, Mercor prohibits discrimination, harassment, and retaliation based on any combination of protected characteristics. This Policy applies to all areas of employment, including recruitment, hiring, training, promotion, compensation, benefits, discipline, termination, and all other privileges, terms, and conditions of employment. This Policy and the law prohibit employment discrimination against any employee or applicant based on any legally protected status.