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Mercor is an AI data company on a mission to organize human intelligence to power the AI economy. The company operates a platform where millions of domain experts train frontier AI models, generating over $4 million per day in expert compensation. Mercor is a profitable Series C company valued at $10 billion, with offices in San Francisco, NYC, and London.
The Applied AI organization builds the systems that convert human expertise into training data for frontier models. This includes task pipelines, expert workflows, evaluation infrastructure, and supporting services. The backend systems must remain correct, fast, and observable while handling rapidly growing volume.
As a Backend Software Engineer, you will own services within this stack, designing data models, building APIs, and creating data pipelines that move work through the platform. This is a hands-on build role where you take a loosely scoped problem, make design decisions, ship to production, and own the system afterward.
Key responsibilities include:
- Design, build, and operate backend services including APIs, data models, background jobs, and connecting pipelines
- Own features end-to-end: scope, design, code, instrument, and maintain in production
- Build and tune high-throughput data and job pipelines with queuing, batching, idempotency, retries, and backpressure
- Optimize system performance and reliability through failure recovery, profiling, caching, and latency/error/cost budgeting
- Instrument systems with observability, metrics, logging, tracing, and proactive alerting
- Manage tens of thousands of containers, sandbox environments, and resource allocation using Terraform
- Participate in on-call rotation, debug production incidents, and document learnings in RCCAs
- Write design docs and provide code review; technical decisions are made in writing with full team participation
- Collaborate with product, operations, and research teams to translate ambiguous requirements into shipped systems
You'll work with a talent-dense engineering team that will challenge your thinking and push you to grow quickly into owning larger system surfaces.
REQUIREMENTS:
- 2–5 years of professional backend engineering experience building and operating production systems
- Strong fundamentals: data structures, algorithms, concurrency, and clear code
- Hands-on API design experience (REST, gRPC, or GraphQL) with understanding of versioning, contracts, and backward compatibility
- Solid database skills: relational data modeling, indexing, query performance, transactions, isolation, and safe migrations
- Familiarity with at least one NoSQL or key-value store and when to use it
- Practical experience with distributed systems basics: queues, event streams, caching, idempotency, rate limiting, partial failure design
- Experience with data orchestration and workflow management systems (Airflow, Temporal, Dagster)
- Ability to debug lower-level infrastructure issues (containers, permissions, logs, traces)
- Production experience: containers, CI/CD, monitoring, alerting, debugging under real traffic
- Comfort with ambiguity; ability to take loosely defined problems and develop plans
- Genuine excitement for agentic development and modern AI tools (Claude Code, Cursor, Copilot); passion for writing good code
- Clear written and verbal communication; high ownership, pragmatism, bias toward shipping
NICE TO HAVE:
- Experience building or integrating LLM-backed services in production (evaluation, orchestration, serving)
- Familiarity with AI infrastructure providers (Modal, Fireworks, Baseten, Temporal)
