Role : AI/ML Engineer - Generative AI & Agentic AI

We are looking for an experienced AI/ML Engineer with strong hands-on experience in Generative AI, LLMs, RAG, and Agentic AI. The ideal candidate will be responsible for designing, developing, and deploying scalable enterprise-grade AI applications and intelligent agent-based solutions.

Key Responsibilities :

- Design and develop Generative AI and LLM-based applications for enterprise use cases.

- Build and implement RAG (Retrieval-Augmented Generation) workflows using enterprise data sources.

- Develop AI Agents and multi-agent systems using frameworks such as LangGraph, CrewAI, or PydanticAI.

- Develop effective prompt engineering strategies and optimize LLM performance.

- Build scalable AI solutions using Python and modern AI/ML frameworks.

- Integrate AI applications with REST APIs, WebSockets, and event-driven architectures.

- Work with Databricks and cloud-based AI platforms to develop and deploy AI solutions.

- Implement production-ready CI/CD pipelines using Jenkins and Git.

- Collaborate with product, engineering, and business teams to translate requirements into AI-driven solutions.

- Ensure AI applications are scalable, secure, reliable, and production-ready.

Must-Have Skills :

- 7+ years of experience in AI/ML or software engineering with relevant AI experience.

- Strong hands-on experience with Python.

- Strong experience in Generative AI and LLMs.

- Hands-on experience building RAG workflows and LLM applications.

- Experience with Agentic AI / AI Agents.

- Experience with one or more agent frameworks: LangGraph, CrewAI, PydanticAI.

- Strong understanding of Prompt Engineering.

- Experience with Databricks and Cloud AI platforms.

- Strong knowledge of REST APIs, WebSockets, and event-driven architecture.

- Experience with Jenkins CI/CD and Git.

- Experience developing and deploying enterprise AI applications.

Good to Have :

- Experience with multi-agent architectures and orchestration.

- Knowledge of vector databases and embedding technologies.

- Experience with LLM evaluation, observability, and performance optimization.

- Understanding of AI security, governance, and responsible AI practices.

- Experience working with Azure AI Foundry, AWS Bedrock, or Google Cloud AI platforms.