Tech Lead, Systems & Platform Applied AI

mercor· Engineering
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📍 San FranciscoFullTime💰 USD 250K–500K

About this role

About Mercor

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

Frequently Asked Questions

What is the salary for the Tech Lead, Systems & Platform Applied AI role at mercor?
The listed salary for this Tech Lead, Systems & Platform Applied AI position at mercor is USD 250K–500K. This is an FullTime role.
Where is the Tech Lead, Systems & Platform Applied AI position at mercor located?
This Tech Lead, Systems & Platform Applied AI role at mercor is based in San Francisco. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Is the Tech Lead, Systems & Platform Applied AI role at mercor full-time or part-time?
This is listed as a FullTime position. It is posted as a Tech Lead, Systems & Platform Applied AI role in the Engineering department at mercor.
Which team or department does the Tech Lead, Systems & Platform Applied AI at mercor belong to?
This Tech Lead, Systems & Platform Applied AI position is part of the Engineering department at mercor. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Tech Lead, Systems & Platform Applied AI position at mercor?
Click the "Apply Now" button on this page. You will be redirected to mercor's official application portal hosted on ashby where you can submit your application directly.
When was the Tech Lead, Systems & Platform Applied AI job at mercor posted?
This Tech Lead, Systems & Platform Applied AI position at mercor was posted on Sep 24, 2026. Apply as soon as possible — early applications are often reviewed first.
Tech Lead, Systems & Platform Applied AI
mercor · 💰 USD 250K–500K
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You'll be redirected to mercor's official application page on Ashby ATS.