Role Overview

We are looking for a hands-on AI Engineer to develop context-aware AI solutions, investigate intelligent vehicle architectures, and build memory frameworks for agentic AI systems.

Key Responsibilities

- Context Engineering & Benchmarking: Develop context-aware AI solutions, RAG/GraphRAG pipelines, and evaluation frameworks to measure accuracy, latency, and reliability.
- Intelligent Car Architecture: Investigate AI-driven vehicle architectures, develop PoCs, and implement test scenarios to validate intelligent vehicle functions.
- Agentic AI Memory: Design and implement short-term, long-term, and persistent memory mechanisms for AI agents.
- AI Integration: Build scalable agentic workflows integrating LLMs, APIs, tools, and external systems.
- Testing & Optimization: Develop automated test scenarios, benchmark AI performance, and optimize system efficiency.

Must-Have Technical Skills

- Robust programming experience in Python.
- Minimum of 3 years Hands-on experience with GenAI, LLMs, Agentic AI, and RAG.




- Experience with LangGraph, LangChain, or similar agentic frameworks.
- Knowledge of context engineering, agent memory, and semantic retrieval.
- Experience with vector databases (FAISS, ChromaDB, Weaviate, etc.).
- Experience in AI evaluation, benchmarking, and test automation.
- Understanding of AI system architecture, REST APIs, and MCP.

Good-to-Have Skills

- Knowledge of automotive software architecture and intelligent vehicle systems.
- Experience with GraphRAG, knowledge graphs, and Neo4j.
- Exposure to cloud platforms - AWS Bedrock, Azure AI, or similar platforms.
- Familiarity with automotive simulation and scenario-based testing.

Qualifications

- Bachelor's/Master's degree in Computer Science, AI, or related engineering discipline.
- Strong problem-solving skills with the ability to independently investigate, prototype, and implement AI solutions.

📌 AI Engineer -Agentic AI & Context Intelligence - AIML (Bengaluru)
🏢 BMW TechWorks
📍 Bengaluru