Data Scientist

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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