Role Overview

We are looking for a hands-on AI Agent Developer to build and integrate GenAI/Agentic AI solutions for enterprise applications. The ideal candidate should have solid Python development skills and practical experience with LLMs, RAG, AI agents, APIs, and cloud platforms.

Key Responsibilities

- Develop AI agents and agentic workflows using Python.
- Build LLM-powered applications using OpenAI/Azure OpenAI, Gemini, Claude, or similar models.
- Develop RAG pipelines using embeddings, vector databases, and enterprise documents.
- Implement tool/function calling, agent memory, prompt engineering, and structured outputs.
- Work with frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI or Semantic Kernel.
- Integrate AI agents with REST APIs, databases, Jira, Confluence, GitHub and other enterprise systems.
- Develop scalable APIs/services using FastAPI/Flask.
- Implement testing, logging, monitoring, error handling, and AI response validation.
- Deploy AI solutions using AWS/Azure/GCP, Docker and CI/CD.




- Optimize applications for accuracy, latency, token usage, and cost.

Required Skills
- 4–5 years of strong Python development experience.
- 1–2+ years of hands-on Generative AI / LLM / Agentic AI development.
- Strong knowledge of RAG, embeddings, vector databases and prompt engineering.
- Hands-on experience with at least one AI agent framework such as LangGraph/LangChain/LlamaIndex.
- Good understanding of REST APIs, JSON, SQL/NoSQL and microservices.
- Experience with Git and cloud platforms.
- Understanding of LLM security, hallucination handling and prompt-injection risks.
- Strong debugging and problem-solving skills.

Good to Have
- Experience with MCP, Graph RAG, Neo4j or knowledge graphs.
- Experience with LLM evaluation and observability.
- Exposure to multi-agent systems and autonomous workflows.
- Experience integrating AI with enterprise/business applications

📌 AI Agent Developer-Benchmind (India)
🏢 BMW TechWorks
📍 India