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.
