Backend Engineer (Go)

About the client:

Our client is a US-based product development company. They help startups and enterprises build full-stack applications through small, AI-augmented teams that bring product, design and engineering together.

AI is built into how they work, from documentation to coding to decision-making, with humans always in control. Their teams move fast, own outcomes, and care about building things that work.

About the role:

You'll design and build high-performance backend systems in Go, and own them end to end, from the first design to production. You'll work closely with product, design and infra teams to shape APIs, architect services and solve real scaling problems.

We're looking for builders: people who pick up a problem and run with it, think clearly about trade-offs, and stay calm when something breaks. You'll use AI tools every day to move faster, while keeping your own judgement in charge.

What we're looking for

• 4+ years of relevant backend engineering experience
• Hands-on experience building production services in Go
• Strong problem solving, with a solid grasp of data structures, algorithms and system design
• Good understanding of concurrency and performance
• Comfortable with Docker, a cloud platform (GCP or AWS) and CI/CD
• An AI-first way of working: you use tools like Cursor or Codex regularly, write effective prompts, and always check the output yourself
• A builder's mindset: you take ownership and ship
• Clear communication: you can explain a technical problem simply

What you'll do:

• Design and build backend services and APIs in Go
• Own features and systems end to end, from data model and design to rollout and production support
• Write clean, testable, idiomatic code
• Find and fix performance problems through profiling, benchmarking and debugging concurrency issues
• Work across the API, infrastructure and database layers, including deployments and monitoring
• Use AI coding tools like Cursor and Codex to speed up your work, and review what they produce
• Explain technical problems and decisions clearly to product, design and engineering teammates
• Take part in code reviews and help shape the team's engineering culture

Good to have:

• Data tools: Data ingestion tools like Fivetran or Nexla, or data pipeline work with Airflow, Spark or Snowflake
• Coding tests and competitive programming: Ratings on Codeforces, CodeChef, LeetCode or HackerRank, contests like ICPC or Google Kickstart, hackathons, or strong coding assessment scores. These show the problem solving, critical thinking and presence of mind this role needs
• Full-stack: Experience with React or Python
• Infra: Kubernetes, Helm, Terraform, or GitOps tools like ArgoCD
• Observability: OpenTelemetry, Grafana, Prometheus or Datadog
• Data and messaging: PostgreSQL, Redis, Kafka, NATS, or event-driven systems
• AI systems: Building AI features in production, such as RAG or agents
• Side projects: Open-source work, personal projects or a technical blog