Role Summary

An experienced AI/ML Engineer (6-8 years) with strong expertise in Generative AI, Agentic AI, and AWS cloud technologies. The ideal candidate will design, develop, and deploy scalable AI solutions using Amazon Bedrock, SageMaker, Lambda, LangChain, and LangGraph, while building LLM-powered applications leveraging models such as Claude. The role requires hands-on experience in prompt engineering, RAG, model evaluation, multi-agent workflows, and AI solution architecture, along with the ability to collaborate with cross-functional teams to drive innovation, scalability, security, and enterprise AI adoption.

Key Responsibilities

- Design, develop, and deploy scalable AI/ML and Generative AI solutions on AWS using Bedrock, SageMaker, Lambda, and related services.
- Build and optimize Agentic AI applications using LangChain and LangGraph, including multi-agent workflows and orchestration.
- Develop LLM-powered solutions leveraging Claude and other foundation models, with expertise in prompt engineering, RAG, fine-tuning, and model evaluation.
- Integrate AI solutions with enterprise applications, APIs, and cloud-native architectures.
- Ensure AI solutions meet scalability, security, performance, and reliability requirements.
- Collaborate with cross-functional teams to define AI strategy, architecture, and best practices.




- Drive innovation through adoption of emerging AI technologies, frameworks, and industry best practices.
- Provide technical leadership, mentoring, and support for AI/ML initiatives.

Required Qualifications

- 6-8 years of experience in AI/ML engineering, with hands-on expertise in Generative AI solutions.
- Robust experience with AWS AI/ML services, including Amazon Bedrock, SageMaker, and Lambda.
- Proficiency in Python and AI/ML frameworks for model development and deployment.
- Hands-on experience with LangChain, LangGraph, and Agentic AI architectures.
- Strong knowledge of LLMs, prompt engineering, RAG, fine-tuning, and model evaluation.
- Experience integrating AI solutions with enterprise applications, APIs, and cloud-native platforms.
- Understanding of AI security, scalability, performance optimization, and best practices.
- Excellent problem-solving, communication, and stakeholder management skills.
- Experience working in Agile delivery environments.

Preferred Qualifications

- AWS AI/ML Certifications.
- Experience with vector databases and multi-agent systems.
- Exposure to MLOps and CI/CD pipelines for AI solutions.
- Knowledge of Responsible AI and AI Governance frameworks.

📌 Ai Ml Engineer (Indore)
🏢 Tata Consultancy Services
📍 Indore