Member of Technical Staff, Tech Lead Applied AI Backend
Mercor · San Francisco
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 our platform are paid over **$4M/day** to train frontier AI models. - **Mercor APEX** benchmark family measures AI’s real-world impact on professional work. - **Mercor Enterprise** brings this infrastructure to Fortune 500 companies—capturing how their best people actually work and translating that expertise into agents. We’re a profitable **Series C** company valued at **$10B**. We work **in-person five days a week** in **San Francisco, NYC, or London**. --- ## About the Role The **Applied AI** org builds systems that turn human expertise into training data for frontier models, including: - task pipelines and expert workflows - evaluation infrastructure - services that tie everything together You’ll work on backend systems that must remain **reliable, fast, and observable** as volume grows. As a **Tech Lead for Applied AI Backend Systems**, you’ll own services across the stack—designing **data models**, building **APIs**, and creating **data pipelines** that move work through the platform. This is a **build role**: take a roughly scoped/ambiguous problem, make design calls, ship to production, and own it afterward. You’ll also mentor engineers and raise the bar for backend design across the org. --- ## What You’ll Do - Own the architecture of the Applied AI backend domain: **core services, data models, orchestration systems, and pipeline execution**. - Set technical direction, while staying hands-on for the hardest parts. - Tackle undefined problems: decide what’s worth building, write designs, ship code, instrument it, and keep it healthy in production. - Build and tune **high-throughput data/job pipelines** (queuing, batching, idempotency, retries, backpressure). - Improve reliability and performance via failure recovery, profiling, caching fixes, and setting **latency/error/cost budgets**. - Own the **design review bar** across the org; mentor senior engineers and make tradeoffs clear to leadership. - Provision and manage infrastructure as code using **Terraform**; manage and launch **10s of thousands of containers**, sandbox environments, and resource allocation. - Participate in on-call for systems you own; debug incidents and write **RCCA** writeups. - Drive cross-functional alignment with product, operations, and research to turn ambiguous requirements into shipped systems. --- ## What We’re Looking For - **8+ years** of professional backend engineering experience building and operating production systems. - Track record owning architecture across multiple teams with decisions that “aged well.” - Experience mentoring **senior** engineers. - Strong backend fundamentals: data structures, algorithms, concurrency, and clear code for others to maintain. - Hands-on API design experience (**REST, gRPC, or GraphQL**) with versioning/contract/backward compatibility. - Solid database skills: relational modeling, indexing, query performance, transactions/isolation, and safe migrations. - Distributed systems expertise: queues/event streams, caching, idempotency, rate limiting, partial failure design. - Experience with data orchestration/workflow systems (e.g., **Airflow, Temporal, Dagster**). - Comfort digging into infrastructure details (containers, permissions, logs, traces) to find root causes. - Production exp
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