Ds

Data Scientist \- - - - - - - - - - - - MISSION: The GenAI Data Scientist designs, builds, evaluates, and deploys Generative AI solutions, with strong focus on GenAI agents and agentic workflows. He/she is responsible for: \* Understanding business needs and converting them into GenAI agent use cases \* Building GenAI agents using LangGraph or similar agentic frameworks \* Designing workflows with tool calling, routing, memory, state management, guardrails, and human escalation \* Connecting agents with enterprise data, APIs, databases, applications, and automation tools \* Building and optimizing RAG knowledge stores when knowledge retrieval is required \* Developing clean, modular, scalable, and deployment-ready Python code \* Evaluating agents for accuracy, reliability, hallucination risk, latency, cost, and user experience \* Working with data, platform, and software engineering teams to move GenAI solutions to production KEY EXPECTED ACHIEVEMENTS: \* Business need is translated into a clear GenAI agent solution \* Agent architecture, workflow, tools, memory, prompts, and guardrails are designed and documented \* Agentic workflows are built, tested, and optimized using LangGraph or similar frameworks \* RAG knowledge stores are implemented and optimized when required \* Python code is modular, testable, maintainable, and production-ready \* The solution is deployed with logging, monitoring, error handling, access control, and cost control \* Results, limitations, risks, and usage guidelines are clearly presented to business and technical stakeholders \* Source code, prompts, configuration, and documentation are delivered \* Peer reviews are organized to ensure quality, scalability, and reliability