Member of Technical Staff, 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. - Our **APEX benchmark** family measures AI’s real-world impact on professional work. - **Mercor Enterprise** brings this infrastructure to Fortune 500 companies—capturing how top people actually work and translating that expertise into agents. We’re a profitable **Series C** company valued at **$10B**, and we work **in-person five days a week** in **San Francisco, NYC, or London**. --- ## About the Role (Applied AI — Backend Systems) 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 join a build-focused team creating backend systems that must stay **correct, fast, and observable** as volume grows. As a **Software Engineer on Backend Systems**, you’ll own services across the stack—designing data models, building APIs, and creating data pipelines that move work through the platform. --- ## What You’ll Do - **Design, build, and operate** backend services: APIs, data models, background jobs, and pipelines. - **Own features end-to-end**: scope → design → ship → instrument → keep healthy in production. - Build and tune **high-throughput data/job pipelines** (queuing, batching, idempotency, retries, backpressure). - Improve **speed and reliability** with failure recovery, hotspot profiling, and cost/token attribution. - Add **observability**: metrics, logging, tracing, and proactive alerts. - Work with modern tools, libraries, and frameworks. - Manage and launch **10s of 1000s of containers/sandbox environments**, including resource allocation and system health. - Use **Terraform** for infrastructure as code. - Participate in **on-call**, debug production incidents, and write **RCCA** write-ups. - Write clear **design docs** and contribute to technical decisions in writing. - Partner with **product, operations, and research** to turn ambiguous requirements into shipped systems. --- ## What We’re Looking For - **2–5 years** of professional backend engineering experience building and operating production systems. - Strong backend fundamentals: data structures, algorithms, concurrency, and maintainable code. - Hands-on **API design** experience (REST, gRPC, or GraphQL) with versioning/compatibility. - Solid database skills: relational modeling, indexing, query performance, transactions/isolation, and safe migrations. - Practical distributed systems experience: queues/event streams, caching, idempotency, rate limiting, partial failure design. - Experience with **data orchestration/workflow systems** (e.g., Airflow, Temporal, Dagster). - Ability to dig into infrastructure details (containers, permissions, logs, traces) and debug under real traffic. - Experience running services in production (containers, CI/CD, monitoring/alerting, incident debugging). - Comfort with ambiguity and strong ownership. - Excitement for **agentic development** and modern AI dev tools (e.g., Claude Code, Cursor, Copilot). - Clear written and verbal communication. --- ## Nice to Have - Experience building/integrating **LLM-backed services** in production (evaluation, orchestration, or serving). - Famil
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