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The role combines Python backend engineering, API development, data processing, and applied AI/LLM workflows.\n\nYou will work closely with engineering, product, QA, and domain experts to convert complex requirements into reliable, scalable, and production-ready solutions.\n\nKey Responsibilities:\n\n- Design, develop, and maintain scalable FastAPI/Python backend services and REST APIs.\n\n- Build LLM/RAG-based applications, including prompt workflows, structured outputs, retrieval, grounding, and guardrails.\n\n- Develop rule-based validations and workflows with proper traceability and auditability.\n\n- Build reliable Celery-based background jobs with retries, monitoring, and failure recovery.\n\n- Design data models and optimise PostgreSQL/SQL queries, caching, latency, and application performance.\n\n- Write unit and integration tests using pytest and maintain high engineering standards.\n\n- Contribute to Docker, Git, CI/CD, observability, security, and cloud deployments.\n\n- 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problem-solving skills.\n\n- Good communication and ability to work with both technical and non-technical stakeholders.\n\n- Interest in sustainability, climate technology, ESG, LCA, or carbon accounting is preferred.\n\nGood to Have:\n\n- Experience with LangChain, LlamaIndex, or similar LLM frameworks.\n\n- Knowledge of LLM evaluation, hallucination control, retrieval quality, and human-in-the-loop workflows.\n\n- Experience with vector databases, search/ranking systems, Pandas, NumPy, or data-processing workloads.\n\n- Exposure to Sentry/monitoring, structured logging, microservices, Kubernetes, or infrastructure-as-code.\n\nSkills\nBackend Architecture, Python, FastAPI, Machine Learning, LLM, 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