AI/ML Engineer – Generative AI & Agentic AI
Experience: 8+ Years
Location: Bangalore
Employment Type: Full-Time
Job Description
We are looking for an experienced AI/ML Engineer with 8+ years of hands-on experience in Generative AI, Large Language Models (LLMs), RAG, and Agentic AI to design, develop, and deploy enterprise-grade AI solutions.
The ideal candidate should have strong expertise in Python, LLM applications, AI agents, RAG workflows, cloud AI platforms, and enterprise AI application development.
Key Responsibilities
- Design and develop scalable Generative AI and Agentic AI applications.
- Build and implement LLM-based solutions and RAG pipelines for enterprise use cases.
- Develop AI agents and multi-agent workflows using LangGraph, CrewAI, PydanticAI, or similar frameworks.
- Perform prompt engineering and optimize LLM performance for various business use cases.
- Integrate AI applications with enterprise systems using REST APIs, WebSockets, and event-driven architectures.
- Work with Databricks and cloud-based AI platforms to build and deploy AI/ML solutions.
- Develop production-ready, scalable, and secure enterprise AI applications.
- Implement CI/CD pipelines using Jenkins and manage source code using Git.
- Collaborate with data scientists, software engineers, and business teams to deliver AI-driven solutions.
- Monitor, troubleshoot, and continuously improve AI applications in production.
Must-Have Skills
- 8+ years of experience in AI/ML engineering or related roles.
- Strong hands-on experience in Generative AI, LLMs, and Agentic AI.
- Strong proficiency in Python.
- Hands-on experience with RAG workflows and LLM application development.
- Experience with AI agent frameworks such as LangGraph, CrewAI, or PydanticAI.
- Strong knowledge of Prompt Engineering.
- Experience with Databricks and Cloud AI platforms.
- Strong understanding of REST APIs, WebSockets, and event-driven architecture.
- Experience with Jenkins CI/CD and Git.
- Experience developing and deploying enterprise-grade AI applications.
- Strong understanding of software development, testing, deployment, and production support.
Good to Have
- Experience with multi-agent systems and Agentic AI architectures.
- Knowledge of LLMOps/MLOps and AI application monitoring.
- Experience with vector databases and embedding models.
- Experience with Azure AI, AWS, or Google Cloud AI services.
- Knowledge of AI security, governance, and responsible AI practices.