Backend Engineer
Build robust backend systems for API ingress, auth, billing, observability, and the zero-knowledge endpoint production teams rely on.
You will build the backend systems that make one endpoint feel durable: APIs, auth, billing, observability, and product data.
About Direct Inference
Direct Inference is the endpoint that does everything frontier models can do. Customers bring the SDK and model id they already use; Direct Inference handles capability, quality, cost, latency, failover, and provider churn behind the scenes.
The important product constraint is zero-knowledge: customers never see which model, provider, or version served a request. That lets them build on a stable surface while the model market keeps moving underneath it.
What you'll own
- Build and harden API ingress, dashboard services, auth/session flows, billing paths, usage storage, and observability systems.
- Design data models and service contracts that keep customer-facing behavior stable as the platform evolves.
- Improve tests and operational checks for request-path behavior, billing correctness, and dashboard accuracy.
- Partner with frontend and product engineering on customer-visible workflows.
- Work with reliability and inference engineering to keep backend systems resilient under production traffic.
Projects you might ship
- Harden an API, billing, or auth workflow that sits on the critical path for customer traffic.
- Improve dashboard data correctness by tightening the contract between request logging, storage, and frontend services.
- Build a backend feature that helps customers understand spend, usage, or application-level attribution.
What we're looking for
- You have shipped backend services used in production by real customers.
- You are comfortable with Go or similar backend languages, HTTP APIs, databases, and service design.
- You value correctness in billing, auth, and observability paths.
- You can debug from user report to database row to service behavior.
- You write tests because you know the request path deserves them.
Nice to have
- Experience with Go, SQLite/Postgres, ConnectRPC/gRPC, billing systems, auth/session systems, or API compatibility layers.
- Familiarity with OpenAI-, Anthropic-, or Gemini-shaped API surfaces.
- Comfort balancing compatibility, security, and product simplicity in the same backend path.
Your first 90 days
- Ship a backend improvement to a customer-facing workflow.
- Strengthen one test or observability gap in the request, billing, or dashboard path.
- Own a service-level change from design through deploy verification.
Benefits & support
Built for people doing serious work in a small team.
Interview process
A direct loop with the people doing the work.
Intro
A focused conversation about your background, what you want to build, and where this role should create leverage.
Technical
A practical working session around the kind of problem this role owns. We prefer realistic systems over puzzle interviews.
Team
Meet the people you would work with across product, engineering, reliability, and customer-facing work.
Offer
We align on scope, compensation, start timing, and the first problems you would take on.
Application
Apply for Backend Engineer.
Share the practical context we should know before the first conversation. We read applications for ownership, clarity, and evidence of shipped work.
More openings
Other ways to build Direct Inference.
Forward Deployed Engineer
Engineering · Remote / San Francisco, CA
Work directly with high-intent customers to get production AI workloads running on Direct Inference, then bring the sharp edges back into the product and serving engine.
Senior Inference Engineer
Engineering · Remote / San Francisco
Own and extend the serving engine: the quality, latency, health, and price signals that decide how every request is served.
Platform Reliability Engineer (SRE)
Infrastructure · Remote
Keep one endpoint dependable across a churning set of upstream providers: failover, rate-limit absorption, and the spend caps that fail closed.