Senior Data Scientist

4 days ago

Bengaluru Karnataka India, Karnataka Tavant Full time

About TavantWith 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 ScientistWork Location: BengaluruWork Experience: 7 to12 yearsJob DescriptionWe 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 Responsibilities1.Agentic AI DevelopmentDesign 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 IntegrationDevelop 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 EngineeringBuild 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 & SecurityEnsure compliance with AI governance frameworks (responsible AI, bias mitigation, and security).Apply monitoring, observability, and guardrails for safe agentic execution.5.CollaborationWork 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

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