Description

Must Have Technical/Functional Skills • 7+ years of relevant experience in data science, analytics, machine learning, or AI. • Expertise in statistical modeling, machine learning, generative AI, agentic AI, and natural language processing. • Strong knowledge of LLMs, prompt engineering, RAG, autonomous decision-making frameworks, and human- in-the-loop workflows. • Programming expertise in Python, R, SQL, SAS, or similar analytical tools, with cloud-based or distributed platforms such as Databricks. • Experience with vector databases, semantic search, knowledge graphs, metadata management, enterprise search, and production AI deployment and monitoring. Roles & Responsibilities Design and implement advanced machine learning, generative AI, and agentic AI solutions across structured and unstructured data. · Build and deploy scalable, automated data science products and reusable analytical assets. · Design agentic AI architectures using LLMs, retrieval systems, structured data, APIs, tools, business rules, routing, and approval checkpoints. · Optimize RAG solutions and develop evaluation frameworks covering accuracy, reliability, hallucination risk, latency, cost, safety, and consistency. · Partner with engineering, platform, business, stakeholders, and clients to deploy, monitor, maintain, and communicate production-ready AI solutions. Generic Managerial Skills, If any • Lead complex analytics initiatives and provide technical guidance. • Mentor data scientists and lead code reviews. • Make analytical and architectural decisions and establish technical standards. • Communicate complex analytical findings to technical and non-technical audiences. • Collaborate with stakeholders and clients across strategic, operational, and clinical objectives. Key Words to search in Resume • AI Engineer; Data Scientist; machine learning; statistical modeling; natural language processing. • Generative AI; Agentic AI; LLM; prompt engineering; RAG; autonomous decision-making; human-in-the-loop. • Python; R; SQL; SAS; Databricks; distributed computing; cloud data platforms. • Vector database; semantic search; knowledge graph; metadata management; enterprise search. • Responsible AI; model governance; explainability; bias detection; hallucination evaluation; production AI monitoring

Key Skills

Education

Bachelor's degree