Gen AI Data Scientist

Virtual Drive for Gen AI Data Scientist

Experience: 5-10 years

Job Location: Chennai/ Hyderabad/ Bengaluru/ Mumbai/ Gurgaon/ Pune/ Kolkata

Virtual Drive Date: 29th October 2026

Job Summary:

We are looking for an experienced Data Scientist with strong expertise in Generative AI, LLMs, AI Agents, RAG, and Machine Learning . The role involves developing scalable GenAI applications, conversational AI solutions, predictive models, and end-to-end ML pipelines using Python, LangChain/LangGraph, vector databases, and modern AI frameworks.

Key Responsibilities:

• Develop and deploy GenAI, Machine Learning, and predictive analytics solutions for business use cases.
• Build AI Agents, chatbots, RAG applications , and conversational AI solutions.
• Develop GenAI use cases including code translation, text extraction, summarisation, and SDLC optimisation .
• Perform data analysis, preprocessing, feature engineering, model training, validation, and optimisation.
• Build end-to-end ML/AI pipelines covering development, deployment, monitoring, and retraining.
• Implement LLM evaluation, AI guardrails, hallucination control, PII filtering, HAP, and bias mitigation .
• Develop and integrate APIs and microservices for scalable AI applications.
• Work with engineering, product, analytics, and domain teams to translate business requirements into AI/ML solutions.
• Diagnose end-to-end integration and communication issues involving API Gateways and Istio .
• Communicate analytical insights through dashboards, visualisations, reports, and presentations.

Required Skills:

• Strong hands-on experience with Generative AI, Gemini or open-source LLMs , and LLM application development.
• Experience building AI Agents, Chatbots, and RAG solutions .
• Strong programming skills in Python , with experience using LangChain, LangGraph, and LangSmith .
• Experience with vector databases such as PGVector or Chroma DB .
• Strong understanding of LLMs, prompt engineering, embeddings, and graph-based agent workflows .
• Experience with GenAI evaluation approaches and tools such as RAGAS, DeepEval, and Pegasus .
• Experience developing AI agents using technologies such as LangGraph, ADK, A2A, and MCP .
• Knowledge of AI guardrails , including hallucination mitigation, PII filtering, harmful-content controls, and bias mitigation.
• Hands-on experience with API development and microservices architecture , including API gateways and Istio.
• Understanding of application and GenAI security controls, including rate limiting, spike protection, Denial-of-Wallet mitigation, and DDoS protection strategies .

Good to Have:

• Machine Learning, NLP, predictive analytics
• MLOps, CI/CD, model monitoring
• GCP, React JS, TypeScript
• Responsible AI, data governance, and model explainability