Back
Strong brand, popular Data Scientist title, mid-level appeal create high applicant density.
Role requires specialized GenAI agent and RAG expertise, limiting cross-industry transfer.
Specialized GenAI technical skills and deployment requirements impose moderate filtering.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Translate business needs into Generative AI (GenAI) agent solutions and design agentic workflows with features like tool calling, routing, memory, guardrails, and escalation.
Build, test, and optimize GenAI agents using LangGraph or similar frameworks, including integration with enterprise data, APIs, and automation tools.
Develop modular, scalable, and production-ready Python code with logging, monitoring, error handling, and collaborate with engineering teams for deployment and quality assurance.
Proficiency in building and deploying Generative AI/agentic workflows using frameworks such as LangGraph or similar.
Strong Python programming skills with experience writing scalable, maintainable, modular code.
Experience with Retrieval-Augmented Generation (RAG) knowledge stores and integrating AI agents with enterprise data sources, APIs, applications.
Work Experience Required: Not explicitly mentioned in the JD
Experienced in translating complex business requirements into AI-driven, agentic workflow solutions with clear architecture and documentation.
Skilled in end-to-end GenAI agent lifecycle including design, evaluation (accuracy, latency, hallucination risk), deployment, and optimization.
Able to collaborate effectively with data, platform, and software engineering teams to deliver production-grade AI solutions with robust monitoring and control.