About the Role:

We're seeking an experienced AI Engineer to design and deploy production-grade LLM applications and AI agents. You'll transform complex AI solutions from prototype through production, building scalable agentic workflows and intelligent systems that drive real-world impact.

Key Responsibilities:

- Design and implement intelligent agents and workflows using frameworks like LangChain, LangGraph, or similar technologies.

- Engineer sophisticated multi-step workflows incorporating tool calling, structured outputs, state management, memory systems, and dynamic loops.

- Develop robust RAG systems including embeddings, vector search, retrieval optimisation, and intelligent reranking.

- Build comprehensive evaluation frameworks to assess accuracy, reliability, latency, and cost efficiency.

- Establish production-ready observability, guardrails, logging, and error handling mechanisms.

- Own the end-to-end journey of AI solutions from initial prototype to full-scale production deployment.

Required Qualifications:

- Python proficiency is essential.

- Strong software engineering fundamentals: OOP principles, asynchronous programming, REST APIs, and robust error handling.

- Proven hands-on experience with LLM and AI agent development.

- Expertise in prompt engineering, loop design, and agentic graph architecture.

- Advanced knowledge of tool calling, function calling, structured outputs, and context/memory management.

- Deep understanding of RAG systems, embeddings, vector search, and retrieval techniques.

- Production experience with LangChain, LangGraph, LlamaIndex, or equivalent frameworks.

- Proficiency with REST APIs and backend service architecture.

- Experience with vector databases (pgvector, Pinecone, Weaviate, Qdrant, or similar).

- Hands-on Docker and cloud infrastructure expertise.

Preferred Qualifications:

- Experience with LangSmith or equivalent observability platforms.

- Knowledge of Model Context Protocol (MCP).

- Expertise in agent evaluation, benchmarking, and automated testing.

- Familiarity with event-driven and asynchronous architectural patterns.

Total Experience: 3 - 6+ years of software engineering experience with hands-on LLM and Generative AI development.