Design, build, and operationalize AI driven solutions for global Analytics organization.
Develop and implement autonomous agents for data validation, reporting, document processing, and domain workflows.
Build distributed data pipelines and develop APIs for AI-powered applications.
Contribute to CI/CD workflows for AI models – deployment, testing, monitoring.
Collaborate with analytics, product, and engineering teams to define AI solutions.

8–12 years of experience in AI/ML engineering, data science, or software engineering, with at least 4 years focused on GenAI.
Strong programming expertise in Python, distributed computing using PySpark, and API development.
Hands on experience with LLM frameworks (LangChain, LangGraph, Transformers, OpenAI/Vertex/Bedrock SDKs).
Experience developing AI agents, retrieval pipelines, tool calling structures, or autonomous task orchestration.
Solid understanding of GenAI concepts: prompting, embeddings, RAG, evaluation metrics, hallucination identification, model selection, fine tuning, context engineering.
Experience with cloud platforms (Azure/AWS/GCP), containerization (Docker), and CI/CD pipelines for ML/AI.
Strong problem solving, system design thinking, and ability to translate business needs into scalable AI solutions.
Excellent verbal, written communication and presentation skills.

Data Scientist

Key skills