Backend API Engineer

Experience Requirements

• 
  

  8+ years of overall experience building and operating backend APIs in production environments



• 
  

  Minimum 4 years of hands-on experience with FastAPI specifically (not just general Python API frameworks)



• 
  

  Demonstrated experience owning services end-to-end — design, development, deployment, and monitoring



• 
  

  Prior experience mentoring engineers or leading technical design discussions is a plus

• Design and develop high-performance RESTful APIs using FastAPI with clean, validated schemas via Pydantic

• Architect scalable backend systems, making sound trade-offs on performance, reliability, and maintainability

• Implement multi-layer caching (Redis + in-memory L1 cache) to optimize latency and throughput

• Build secure authentication/authorization flows using JWT and OAuth2

• Integrate with external and internal services using async HTTP clients (HTTPX)

• Design and consume message queues for asynchronous and event-driven processing

• Implement standardized, consistent error handling following RFC 9457

• Write efficient, optimized SQL queries and review database interaction patterns

• Drive system design discussions and review architecture proposals across teams

• Write unit/integration tests and uphold high code quality and observability standards

Required Skills (Mandatory)

• FastAPI

  4+ years of deep, hands-on production experience — routing, dependency injection, async endpoints, middleware, background tasks

• Pydantic

  Strong command of data validation, serialization, custom validators, and schema design (v1/v2)

• Redis

  Caching strategies, pub/sub, session/token storage, expiry and eviction policies

Core Skills (Working Knowledge Expected)

• System Design — ability to architect scalable, fault-tolerant, high-throughput backend systems

• Authentication & Authorization — OAuth2, RBAC, secure API access patterns

• JWT — token issuance, validation, refresh flows, and security best practices

• HTTPX — async HTTP client usage for reliable service-to-service communication

• API Design — RESTful principles, versioning, rate limiting, backward compatibility

• Message Queues — experience with Kafka, RabbitMQ, SQS, or Celery for async processing

• L1 Cache Handling — in-memory/application-level caching alongside Redis (L2) for low-latency reads

• Exception Handling (RFC 9457) — standardized "Problem Details for HTTP APIs" error responses

• SQL — strong working knowledge of relational databases (PostgreSQL/MySQL), query optimization, and ORM usage (SQLAlchemy)