Senior AI/ML Engineer Generative AI (6+ Years)

About the Role We are looking for a Senior AI/ML Engineer with 6+ years of experience in Machine Learning, Artificial Intelligence, and Generative AI to build scalable, enterprise-grade AI solutions. The ideal candidate should have hands-on experience with AI Agents, LLMs, RAG workflows, and cloud-native deployments. Experience: 6+ Years Employment Type: Full-Time Location: Bengaluru (on-site) Key Responsibilities Build AI agents using frameworks such as LangGraph, AutoGen, CrewAI, and PydanticAI. Design and optimize prompt engineering workflows for LLMs including GPT, Claude, and LLaMA. Develop modular and reusable components for agent orchestration and task automation. Build and deploy AI/ML models using Databricks and Azure ML. Develop APIs, WebSockets, and event-driven architectures for real-time AI services. Work with CI/CD pipelines using Jenkins for automated testing and deployment. Utilize AI-assisted development tools such as GitHub Copilot, Windsurf, and Codeium to improve development efficiency. Maintain code quality, documentation, and development best practices using Git, Jira, and Confluence. Required Skills & Qualifications 6+ years of experience in Machine Learning, Artificial Intelligence, or related fields. 6+ years of experience building enterprise-grade Generative AI applications with a strong understanding of RAG workflows. Strong proficiency in Python and modern software development practices. Hands-on experience with Large Language Models (LLMs) and prompt engineering. Experience building AI agents using at least one of the following frameworks: LangGraph, CrewAI, or PydanticAI. Familiarity with Databricks, Azure ML, and cloud-native deployment strategies. Good understanding of REST APIs, WebSockets, and event-driven architectures. Experience with SDLC best practices, Agile methodologies, Jenkins, and Git. Comfortable working with AI-powered development tools for rapid prototyping. Preferred Skills Exposure to MLOps/LLMOps workflows and model monitoring. Knowledge of enterprise security, compliance, and governance practices for AI systems. Strong analytical, communication, and problem-solving skills. Ability to work effectively in cross-functional teams and adapt to evolving technologies and priorities.