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PocketPills

Posted 17 Sep 2026

AI Engineer (Agentic AI & LLM Applications)

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Employment
Full time
Team
Data Science & Analytics
Posted
17 Sep 2026

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.


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.


Requirements:

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

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