AI Agent Developer-Benchmind

BMW TechWorks India Private Limited; Pune District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

BMW TechWorks India Private Limited is seeking an AI Agent Developer to build and integrate GenAI/Agentic AI solutions for enterprise applications. The candidate will leverage Python, LLMs, RAG, and cloud platforms to deliver scalable AI agents and workflows.

The role involves implementing tool calling, memory, and prompt engineering, with integration to REST APIs, databases, Jira/Confluence, and GitHub. Experience with LangChain/LangGraph/LlamaIndex is beneficial, as is deployment on

Qualifications

• 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.

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.

Skills

Python development

Generative AI/LLM

RAG & embeddings

AI agent framework

REST APIs

Cloud platforms

Debugging

Tools

LangChain

LlamaIndex

LangGraph

Neo4j

Docker

FastAPI/Flask

Job description

Agent Development Application Development Rest API Python JSON

Job Description

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 strong 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