PocketPills - AI Engineer - LLM &amp Agentic AI

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.
  
  

(ref:hirist.tech)