AI Engineer — Agentic AI & LLM Applications

Pocketpills; Gurugram District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Pocketpills is seeking an AI Engineer to design and deploy production-grade LLM applications and AI agents. You will translate prototypes into scalable systems, building agentic workflows that drive real-world impact.

You will work with LangChain, LangGraph, and vector databases to build robust RAG pipelines, with a focus on observability, memory management, and reliable tool-using architectures.

Qualifications

• 3–6+ years of software engineering experience with hands-on LLM and Generative AI development.
• Strong fundamentals in Python and modern software engineering practices.

Responsibilities

• Design and implement intelligent agents and workflows with LangChain or LangGraph.
• Engineer multi-step workflows with tool calls, outputs, memory, and dynamic loops.
• Develop robust RAG systems with embeddings, vector search, and retrieval optimization.
• Build evaluation frameworks for accuracy, latency and cost efficiency.
• Establish production-ready observability, guardrails and error handling.
• Own end-to-end AI solutions from prototype to production.

Skills

Python

Async programming

REST APIs

Error handling

LLM/Agent development

Prompt engineering

Tool calling

Vector tech concepts

Production-grade software

Memory management

Tools

LangChain

LangGraph

LlamaIndex

pgvector

Pinecone

Weaviate

Qdrant

Docker

Cloud infrastructure

Job description

AI Engineer - Agentic AI & LLM Applications

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 optimization, 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

Experience

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