Backend Software Engineer

About the role

You will build the server-side systems that power products used by thousands of people: APIs, data pipelines, background workers, and the business logic at the heart of the application. Backend engineers here own their services completely, from database schema to deployment configuration to production monitoring and on-call. You will design for reliability and scale from the start, because the frontend, the mobile apps, and the customers all depend on your systems behaving correctly under load. Deep thinking about data modeling, API design, and failure modes is the daily work, and operational excellence is the standard.

What you will achieve

• Design and build reliable backend services handling real production traffic with clean APIs, solid data models, and comprehensive automated tests
• Deliver measurable latency and throughput improvements through profiling, query optimization, caching strategy, and architectural refinement
• Build resilient integrations with third-party services: retries with backoff, circuit breakers, timeouts, and graceful degradation designed in from the start
• Reduce operational burden through better observability: meaningful metrics, actionable alerts, and runbooks that make on-call rotations humane
• Drive data integrity through careful migration planning, transactional correctness, and validation checks that catch corruption before it spreads

What you will bring

Must-haves

• 2 to 5 years building backend services in production with real traffic volumes and operational responsibility for uptime
• Strong skills in a backend language such as Python, Go, or Java, with attention to concurrency models and performance characteristics
• Experience designing REST APIs or gRPC services with versioning, pagination, error handling, and authentication built in
• Deep relational database knowledge: schema design, indexing strategy, query optimization, transactions, and migration safety
• Familiarity with caching systems (Redis, Memcached) and message queues (SQS, Kafka, RabbitMQ) applied appropriately to real problems
• Understanding of distributed systems basics: retries, idempotency, eventual consistency, and systematic failure mode analysis
• BS in Computer Science or equivalent experience

Nice-to-haves

• Experience with event-driven architectures and stream processing operating at meaningful production scale
• Familiarity with Kubernetes deployments, service meshes, or serverless platforms in production
• Knowledge of data pipeline tools such as Airflow, dbt, or stream processing frameworks
• Experience with database replication, partitioning strategies, or read-replica architectures