Agentic AI engineer - AIML

BMW TechWorks India Private Limited; Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

BMW TechWorks India Private Limited seeks an experienced AI/ML engineer to design, develop, and deploy GenAI-powered workflows and multi-agent systems. You will build and scale agentic AI applications end-to-end across architecture, orchestration, and cloud deployment, ensuring robust production readiness.

The role requires hands-on experience with AWS/Azure services, containerization, and MLOps, plus strong Python skills and excellent communication in English.

Qualifications

• 4-7 years of experience in AI/ML research and development with Generative AI focus.
• Proven hands-on experience building and deploying Agentic AI frameworks and multi-agent systems in production.

Responsibilities

• Design, develop, and refine Agentic AI workflows that form the core of AI-driven products and services.
• Own design and delivery of GenAI-powered applications translating business problems into agent-driven solutions.
• Deploy, scale, and operate AI applications on AWS/Azure with containerization and cloud-native patterns.
• Embed AI agents into automotive software pipelines for real-time anomaly detection and automated regression analysis.
• Develop and maintain AI-based tools for model-based development, system diagnostics, code generation, and CI.
• Drive AI initiatives with structured processes, ensuring predictability and traceability from requirements to deployment.
• Stay abreast of agentic AI trends and cloud-native services, proposing integrations to advance capabilities.

Skills

Generative AI

Agentic AI

Python

Cloud deployment

CI/CD

MLOps

Communication

English

Tools

Docker

Kubernetes

SageMaker

Azure ML

Bedrock/Azure OpenAI

LangChain/LangGraph

Job description

• Join our team to industrialize sophisticated cutting-edge AI for our next generation of Innovations at BMW.
• The role involves designing, developing, and refining Agentic AI based workflows that will form the core of our innovative AI-driven products and services.
• The ideal candidate will possess deep expertise in generative AI practices, with the ability to build and scale Agentic AI applications end-to-end — from architecture and orchestration to cloud deployment and production operation.
• Own the design and delivery of GenAI-powered applications, translating business problems into robust, agent-driven solutions with measurable outcomes.
• Deploy, scale, and operate AI applications on cloud platforms (AWS/Azure), leveraging managed AI/ML services, containerization, and cloud-native architecture patterns.
• Embed AI agents into automotive software pipelines to enable adaptive behaviours, such as real-time anomaly detection during unit testing or automated regression analysis in system validation.
• Develop and maintain AI-based tools for model-based development, system diagnostics, code generation, and continuous integration.
• Drive processes in a structured and organized manner — from requirement gathering through to deployment — ensuring predictability and traceability across the AI application lifecycle.
• Stay abreast of emerging agentic AI trends and cloud-native AI services, quickly upskilling and proposing integrations that advance our software capabilities.
• In your daily work, you will find yourself in an international and interdisciplinary environment with an agile mindset.
• Our campus offers the cloud infrastructure you need to work productively with large amounts of data and focus on the software for the automobile of the future.

What should you bring along!

• 4-7 years of experience in AI/ML research and development, with a strong focus on Generative AI application creation
• Proven, hands‑on experience building and deploying Agentic AI frameworks and multi-agent systems in production environments
• Strong hands‑on experience deploying and operating AI/ML applications on AWS and/or Azure — including compute (EC2/Azure VMs), managed AI services (SageMaker/Azure ML, Bedrock/Azure OpenAI), containerization (Docker/Kubernetes), storage, and networking basics
• Proven experience with generative model architectures and techniques, as well as fine‑tuning methods to improve model performance
• Familiar with implementing RAG (Retrieval‑Augmented Generation) architecture for sophisticated AI applications
• Experience setting up CI/CD pipelines for AI application deployment (Jenkins, GitLab CI, or cloud-native pipelines such as AWS CodePipeline/Azure DevOps)
• Demonstrated ability to quickly grasp new tools, frameworks, and emerging cloud/AI concepts, and apply them pragmatically
• Strong process orientation — able to structure and drive complex AI initiatives in an organized, transparent, and repeatable way
• Knowledge of MLOps practices to ensure the robustness and reliability of AI systems in production
• Strong Python programming skills and experience with modern AI frameworks (PyTorch, TensorFlow, LangChain/LangGraph, or similar agentic frameworks)
• Excellent communication and collaboration skills, with the ability to lead and mentor junior team members
• Business fluent knowledge of English (written and spoken)