We are seeking a Data Scientist - GenAI with hands-on experience in Large Language Models (LLMs) to design, build, and operationalize GenAI solutions on the Azure platform. The role combines strong data science foundations with LLM engineering, Azure Databricks, and enterprise-grade GenAI enablement.

Key Responsibilities

Design, build, and deploy LLM‑based GenAI solutions for business use cases.
Develop LLM pipelines including prompt engineering, embeddings, fine‑tuning, and RAG (Retrieval‑Augmented Generation).
Work on LLM catalogs to manage, version, and reuse approved models, prompts, and chains.
Manage LLM endpoints for inference, scalability, access control, and lifecycle management.
Integrate GenAI services via API gateways ensuring security, throttling, and governance.
Implement tracking, monitoring, and observability for LLM performance, cost, latency, and quality.
Enable A2A (Agent to Agent) GenAI integrations and work with MCP (Model Context Protocol)–based patterns where applicable.
Leverage Azure Databricks for data preparation, experimentation, and evaluation using structured and unstructured data.
Collaborate with MLOps and platform teams to productionize models using CI/CD and best practices.
Evaluate LLM outputs for relevance, hallucination control, safety, and business accuracy.
Document solutions and contribute to reusable GenAI standards and assets.

Required Skills & Experience

Core Skills

Strong background in Data Science, Machine Learning, and NLP.
Hands-on experience with LLMs and GenAI (prompt engineering, embeddings, RAG).
Experience working with LLM catalogs, endpoints, and API-based inference.
Solid Python skills for data science and model development.
Experience with Azure Databricks (Delta Lake, MLflow, notebooks).
Understanding of LLM observability, monitoring, and cost optimization.

Platforms & Tools

Azure ecosystem: Azure Databricks, Azure ML, Azure OpenAI (preferred).
Familiarity with endpoint management, API gateways, and secure GenAI integrations.
Exposure to A2A integration patterns and emerging MCP concepts.
Understanding of basic MLOps / LLMOps practices.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related field (or equivalent experience).
Typically 8+ years of experience in Data Science / ML, with recent focus on GenAI / LLMs.
Strong analytical, problem‑solving, and communication skills.

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Data Scientist

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