Role

Data Scientist – GenAI / LLM / Conversational AI

Experience

6+ years total in AI/ML, Data Science, or Software Engineering, including 3+ years focused on GenAI, LLM, RAG, or Conversational AI

Cloud Requirement

Minimum 4 years of hands-on Google Cloud Platform (GCP) experience

Locations

Pune | Hyderabad | Bangalore

Employment Type

Full-time

About the Role

We are looking for an experienced Data Scientist to design, build, and productionize Generative AI and LLM-powered applications on Google Cloud Platform. The ideal candidate combines strong software engineering fundamentals with hands-on expertise in LLM application development, Retrieval-Augmented Generation (RAG), agent orchestration, and enterprise-grade LLM security, delivering scalable and secure conversational AI solutions.

Experience & Qualifications

• 6+ years of overall experience in AI/ML, Data Science, or Software Engineering.
• 3+ years of hands-on experience in GenAI, LLM, RAG implementation, or Conversational AI, including production deployment (LLM productionisation).
• Minimum 4 years of hands-on experience on Google Cloud Platform (GCP).

Must-Have Skills — Generic

• Strong programming skills in Python, with experience building APIs using FastAPI and REST API design.
• Experience with asynchronous processing and building scalable backend services.
• Hands-on LLM application development experience.
• RAG (Retrieval-Augmented Generation) implementation using vector databases.
• Strong grounding in prompt engineering, tool calling / function calling, and structured output generation.
• Working knowledge of LLM security practices, including prompt injection prevention, data leakage protection, access control, and guardrail implementation.

Must-Have Skills — GCP

• Vertex AI & Vector Search: Hands-on experience with Vertex AI, including Vector Search, or equivalent vector database platforms such as Pinecone, Weaviate, FAISS, Chroma, or pgvector.
• Gemini: Practical experience building applications using Google's Gemini models.
• Agent Orchestration: Experience orchestrating agents using ADK (Agent Development Kit), or equivalent frameworks such as LangChain, LlamaIndex, Semantic Kernel, CrewAI, or AutoGen.
• Deployment: Proven experience deploying production workloads on Cloud Run, GKE, or equivalent container/serverless platforms.
• Evaluation: Experience with LLM evaluation using Vertex AI Evals, RAGAS, custom evaluation frameworks, golden datasets, or regression testing methodologies.

Good to Have (Trainable)

• Google Agent Development Kit (hands-on depth).
• Agent Engine / Gemini Enterprise Agent Platform.
• Model Armor for LLM security and safety enforcement.
• Agent observability and tracing tooling.
• Multi-agent architecture design and implementation.
• Human-in-the-loop (HITL) approval workflows.
• Enterprise knowledge graph or enterprise search integration.

Work Location

• Pune
• Hyderabad
• Bangalore