Senior Data Scientist - Agentic AI

About Tavant

With 25+ years of experience building innovative digital products and solutions, Tavant provides impactful results to its customers. It has been the frontrunner in driving digital innovation and tech-enabled transformation across a wide range of industries such as Consumer Lending, Manufacturing, Agtech, Media & Entertainment, and Retail in North America, Europe, and Asia-Pacific. Powered by Artificial Intelligence and Machine Learning algorithms, we help our customers improve their operational efficiency, productivity, speed, and accuracy. Our suite of products and solutions are routinely rated high by the industry.

Ours is a challenging workplace where teams are diverse, competitive, and continually searching for tomorrow's technology and brilliant minds to create it. And we don’t focus just on what we do – we also care how we do it. So, bring your talent and ambition to make a difference. We’ll create a world of opportunities for you.

Job Title

: Senior Data Scientist

Work Location : Bengaluru

Work Experience : 7 to12 years

Job Description

We are seeking Agentic AI Developers to design, build, and deploy next-generation intelligent applications on Microsoft Azure. The ideal candidate will have strong experience in AI / ML development, LLMOps, and Azure AI services, with a focus on creating autonomous, multi-agent workflows that interact with data, APIs, and enterprise systems in real-time.

Key Responsibilities

1.Agentic AI Development

Design and implement autonomous agent workflows using frameworks like LangChain, Semantic Kernel, AutoGen, CrewAI, or LlamaIndex.

Build goal-driven multi-agent systems with planning, reasoning, and tool orchestration.

Implement retrieval-augmented generation (RAG) pipelines with vector databases (Azure AI Search, Pinecone, Weaviate, etc.).

2.Azure Ecosystem Integration

Develop solutions using Azure OpenAI, Azure ML, Cognitive Services, and AI Studio.

Orchestrate pipelines with Azure Functions, Logic Apps, Event Grid, and Data Factory.

Manage compute environments (AKS, Azure Container Apps, or Synapse for analytics workloads).

3.Enterprise AI Engineering

Build scalable APIs and microservices for agent-based applications.

Integrate agents with enterprise data lakes, APIs, and SaaS systems.

Implement MLOps / LLMOps workflows with MLflow, Prompt Flow, and Azure ML pipelines.

4.Governance & Security

Ensure compliance with AI governance frameworks (responsible AI, bias mitigation, and security).

Apply monitoring, observability, and guardrails for safe agentic execution.

5.Collaboration

Work with data scientists, cloud architects, and product owners to transform business use cases into agentic AI solutions.

Stay updated on the latest advancements in

Azure AI, GPT models, multimodal models, and autonomous agents