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 Applied AI org builds the systems that turn human expertise into training data for frontier models, task pipelines, expert workflows, evaluation infrastructure, and the 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 Tech Lead for the Applied AI 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, mentor other engineers on the team and grow them.
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 designs 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 hardest parts yourself.
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.
Own the design review bar for backend work across the org. Mentor senior engineers, make the technical tradeoffs legible to leadership in writing, and raise the standard for how we build.
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
8+ 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.
Experience mentoring senior engineers, not just junior ones.
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
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
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
Skills Required
- 8+ years of professional backend engineering experience building and operating production systems
- Experience owning architecture across multiple teams and making durable technical decisions
- Experience mentoring senior engineers
- Strong fundamentals in data structures, algorithms, concurrency, and maintainable code
- Hands-on API design experience with REST, gRPC, or GraphQL, including versioning, contracts, and backward compatibility
- Strong relational database skills, including data modeling, indexing, query performance, transactions, isolation, and safe migrations
- Familiarity with at least one NoSQL or key-value store
- Deep hands-on distributed systems experience, including queues, event streams, caching, idempotency, rate limiting, and partial-failure design
- Experience with data orchestration or workflow management systems such as Airflow, Temporal, or Dagster
- Ability to troubleshoot lower-level infrastructure issues involving containers, permissions, logs, and traces
- Experience running production services with containers, CI/CD, monitoring, alerting, and real-traffic debugging
- Ability to work effectively through ambiguity and define implementation plans
- Fluency with modern AI development tools such as Claude Code, Cursor, or Copilot
- Strong written and verbal communication, ownership, pragmatism, and bias toward shipping
- Experience building or integrating LLM-backed services in production
- Familiarity with AI infrastructure providers such as Modal, Fireworks, Baseten, or Temporal
Mercor Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Mercor and has not been reviewed or approved by Mercor.
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Fair & Transparent Compensation — Pay is considered competitive across many roles, with clear hourly ranges and an hourly/pay‑per‑task mix designed to align rates with expertise. The structure emphasizes transparent, appropriate pay levels and guarantees payment for legitimate logged time.
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Strong & Reliable Incentives — Payments are processed on a predictable weekly cadence via Stripe/Wise, and some tracks offer additional weekly bonus incentives for top performers. This combination of regular payouts and performance bonuses supports dependable earnings when projects are active.
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Equity Value & Accessibility — Select full‑time roles include generous equity grants alongside cash perks such as relocation and housing bonuses. These elements increase total compensation for those positions.
Mercor Insights
What We Do
We use AI to understand human ability and match talent with the opportunities they're best suited for.

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