We're looking for a Senior Backend Engineer to design and build reliable, scalable backend systems that power our internal platforms and business operations. You'll own systems end to end - from architecture and implementation through deployment, observability and production troubleshooting.
As we expand into AI, you'll also build and integrate LLM-powered capabilities and AI agent workflows into real internal processes.
What You'll Do:
- Design and build backend systems: Own the architecture and development of scalable, reliable backend services and APIs.
- Solve distributed-system challenges: Design for idempotency, concurrency, consistency, retries, failure handling, and asynchronous or event-driven workflows.
- Build production-ready AI systems: Integrate LLM APIs or self-hosted models into backend services, and design the supporting systems for reliability, scalability, observability and maintainability.
- Build AI agent workflows: Tool calling, multi-step workflows, orchestration, and reliable AI-powered automation.
- Ensure performance and reliability: Optimize databases and queries, build observability through logging, metrics and tracing, and troubleshoot production issues.
- Drive engineering practices: Make architecture decisions, improve code quality, run code reviews, and mentor other engineers.
- Bachelor's degree in Computer Science, Software Engineering, Information Technology or a related technical field.
- 4 - 5 years of experience as a Backend Engineer, with strong ownership of production systems.
- Strong experience with at least one backend language such as Go, Python, Java or Node.js.
- Strong understanding of system design, API design and backend architecture.
- Experience with PostgreSQL, MySQL, MongoDB or similar databases, including performance tuning, indexing and transaction handling.
- Experience with message queues or event-driven architecture such as Kafka, RabbitMQ, Pub/Sub or SQS.
- Good understanding of distributed systems, including idempotency, concurrency, consistency, retries and failure handling.
- Experience with observability - logging, metrics and tracing.
- Experience diagnosing and troubleshooting production issues in large-scale or business-critical systems.
- Strong understanding of SOLID principles and Clean Architecture.
- Strong problem-solving skills, and the ability to independently research and evaluate new technologies and approaches.
Nice to Have:
AI / LLM
- Hands-on experience with LLM applications, RAG, AI agents, tool calling or workflow orchestration.
- Experience integrating OpenAI, Claude or other LLM providers, or working with self-hosted open-source models.
- Experience building production-grade AI systems with a focus on reliability, evaluation, observability and scalability. Platform & delivery
- Experience with Kubernetes or cloud-native technologies.
- Experience with AWS, GCP or similar cloud platforms.
- Experience building internal tools or workflow/AI platforms.
