Back End Engineer (Enterprise Efficiency) - Sea Labs

Develop and maintain backend services for enterprise-grade products. Write clean, readable, and well-tested code that follows existing team conventions and coding standards. Collaborate with product managers, frontend engineers, and QA teams across the full development lifecycle – from PRD brief to production release.

Participate in technical design discussions and contribute to technical design documents under guidance from senior engineers. Conduct and participate in code reviews, actively incorporating feedback to improve code quality Test your own work thoroughly before handoff – you will be expected to catch basic issues before QA Communicate clearly with PMs, QA, and peers: provide timely status updates, proactively raise blockers, and ask questions early when requirements are unclear Learn and apply AI-assisted development tools (e.

g., Cursor, ChatGPT, Claude) to accelerate your coding, debugging, testing, and documentation workflows Contribute to AI/LLM integration efforts in backend services where applicable, including API integration and output handling 1–3 years of backend development experience (Java, Go, or Python preferred) Solid fundamentals: data structures, algorithms, OOP/design patterns, REST API design Working knowledge of relational databases (SQL queries, basic schema design, indexing) Familiarity with version control (Git) and basic CI/CD concepts Able to write clean, readable code and follow existing code conventions General AI literacy – understands core AI/LLM concepts and can evaluate where AI capabilities can be practically applied to improve product features or engineering processes Nice-to-Have Technical Skills Experience with microservices or service-oriented architecture Familiarity with caching (Redis), message queues, or containerization (Docker) Exposure to automated testing frameworks (unit tests, integration tests) Proficient in using AI-assisted development tools (e.

g., Cursor, ChatGPT, Claude) to accelerate coding, debugging, testing, and documentation workflows Hands-on experience integrating AI/LLM APIs into backend services (e.g., prompt engineering, API integration, output parsing)