GenAI/RAG Senior Engineer

About the role

The GenAI/RAG Senior Engineer is a hands‑on technical specialist responsible for designing, building, and operating production‑grade Generative AI solutions, including Retrieval‑Augmented Generation (RAG) pipelines, prompt engineering, agent workflows, and LLM orchestration.

Key responsibilities

• Develop and deploy end‑to‑end GenAI systems that integrate vector databases, embedding models, and retrieval components.
• Design, implement, and optimise prompts, chains, and agent workflows for business use cases.
• Conduct model evaluation, testing, and optimisation for quality, latency, cost, and safety.
• Establish engineering best practices, code standards, testing frameworks, and deployment patterns for GenAI projects.
• Integrate GenAI solutions with enterprise APIs, data sources, and existing systems.
• Implement monitoring, logging, and observability for production‑grade AI services.
• Provide technical mentorship, code reviews, and knowledge sharing for junior AI engineers.
• Collaborate with Data Engineers on data pipelines and feature stores supporting GenAI use cases.

Required profile

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science or a related field.
• 8+ years of software engineering experience, with at least 3 years focused on AI/ML and 1+ year on Generative AI/LLMs.
• Proven track record building production RAG systems, prompt engineering, and LLM orchestration.

Required skills

• Python programming
• Vector databases (e.g., Pinecone, Milvus)
• Embedding models and retrieval frameworks
• LangChain, LlamaIndex
• OpenAI, Anthropic, Google AI, Azure OpenAI platforms
• Cloud platforms: AWS, Azure, GCP
• MLOps practices and tooling
• NLP, semantic search, information retrieval concepts