Software Engineer - Applied AI, Systems

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

The Code Data team builds tasks for several frontier benchmarks to create training data for frontier models, using synthetic task pipelines, expert workflows, evaluation infrastructure, and all the systems and services that tie them together. We have synthetic pipelines and modular quality control systems that run in unison to generate highest quality tasks and at scale. All of it runs on backend systems that have to stay reliable, fast, and observable while the volume behind them grows every month.

As a Senior Engineer for the Code Data Backend Systems, you'll own services in that stack: designing the data models, building the APIs, services, Data pipelines that move work through the platform. This is a build role and you'll take a problem that's roughly scoped, ambiguous, make the design calls, ship it to production, and own it afterward with Observability Dashboards and Analytical Metrics.

We're hiring for depth in backend fundamentals rather than any particular domain. If you've built and operated real services, handled the schema migration that couldn't take downtime, found the query that fell over at 10x traffic, designed the retry logic that made a flaky dependency invisible to users, or build a system that recover when things break that's the experience that matters here. You'll work with a talent dense group of engineers who will review your work and push your thinking.

What you will Do

• Own the architecture of the Applied AI backend domain; core services, data models, orchestration systems and the pipeline execution layer that the product and ops team in the org depends on.

• Set the technical direction, then stay hands-on enough to build the bleeding edge and open ended Agentic systems.

• You'll take problems that arrive undefined, decide what's worth building, and own the outcome - the scoping is part of the job, write the design, ship the code, instrument it, and keep it healthy in production.

• Build and tune high-throughput data and job pipelines: queuing, batching, idempotency, retries, and backpressure. Make the system fast and reliable by adding failure recovery in pipelines, profile hot spots, Agent token and cost attribution, caching issues, and set latency, error, cost budgets you actually hold to.

• Provision and manage infrastructure as code using Terraform and at scale. Manage and launch 10s of 1000s of containers, sandbox environments, manage resource allocation and system health.

• Participate in on-call for the systems you own, debug production incidents, and write up what you learn in RCCA.

• Drive XFN alignment across teams through technical judgment and work directly with product, operations, and research partners to turn ambiguous requirements into systems that ship.
  

What we are Looking For

• 3-7+ years of professional backend engineering experience building and operating production systems with a track record of owning architecture across multiple teams and of decisions that aged well.

• Strong fundamentals in backend engineering: data structures, algorithms, concurrency, and writing code that's clear enough for the next person to change.

• Hands-on experience with API design - REST, gRPC, or GraphQL, and an understanding of versioning, contracts, and backward compatibility.

• Solid database skills: relational data modeling, indexing, query performance, transactions and isolation, and safe migrations. Familiarity with at least one NoSQL or key-value store and when it's the right choice.

• Deep, hands-on expertise in distributed systems: queues and event streams, caching, idempotency, rate limiting, and designing for partial failure.

• Experience with Data Orchestration and workflow management systems like Airflow, Temporal, Dagster.

• Be able to roll your sleeves up and dig deeper into the lower level infrastructure issues container, permissions, logs, traces and find the needle in the haystack.

• Experience running services in production: containers, CI/CD, monitoring and alerting, and debugging issues under real traffic.

• Comfort with ambiguity you can take a loosely defined problem, ask the right questions, and come back with a plan. Strong opinions, loosely held.

• Genuine excitement for agentic development and new technology, fluency with modern AI dev tools (e.g. Claude Code, Cursor, Copilot), and a real passion for writing good code.

• Clear written and verbal communication. High ownership, pragmatism, and a bias toward shipping.
  

Nice to Have

• Reinforcement Learning with Verifiable Rewards

• Experience building or integrating with LLM-backed services in production (evaluation, orchestration, or serving).

• Familiarity with AI infrastructure providers like Modal, Fireworks, Baseten, Temporal

Benefits:

• Generous equity grant vested over 4 years

• Health, dental, and vision insurance

• 401(k) with company match

• Unlimited paid vacation and sick days

• Parental leave for birthing and non-birthing parents

• Free mental health services

• $200 monthly wellness reimbursement

• $1.5K monthly meal stipend

• $200 monthly laundry reimbursement

• Free Equinox membership

• Up to $15K relocation bonus

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.