Live opening · Posted 1 day ago

Data Scientist ( Gen AI+ Agentic AI with Dataiku and Snowflake )

Volga Infotech · Mumbai, Maharashtra, India (Remote)
Linkedin Yes
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At a glance

The key details from the original listing.

Posted 1 day ago
CompanyVolga Infotech
LocationMumbai, Maharashtra, India (Remote)
Work modeYes
SourceLinkedin
ListedPosted 1 day ago

About the role

Description supplied by the original job listing.

** We are looking for immediate joiners only. If interested, please email us yoru resume ( resume @volgainfotech.com ) along with details of your CTC, ECTC, Notice period and your experience with GenAi, Agentic, Dataiku and Snowflake ) **
Role Overview
We are seeking a hands-on Data Scientist – Gen AI Consultant with strong expertise in Generative AI, Agentic AI, and enterprise data platforms. The ideal candidate will design, build, and deploy production-grade GenAI and multi-agent systems using Dataiku and Snowflake.
Key Responsibilities
GenAI & Agentic AI Solutions: Design and deploy production-ready Generative AI and Agentic AI workflows.
Agent Architecture & Orchestration: Build AI Agents, write detailed multi-page agent instructions, define tools, and architect multi-agent orchestration for end-to-end task execution.
Platform Integration: Implement and optimize workflows using Dataiku (specifically leveraging LLM Mesh) integrated with Snowflake.
Technical Execution: Walk through projects end-to-end, evaluating tech choices, architecture, trade-offs, and implementation outcomes.
Position Details
Experience Required: 4+ years in Data Science / AI-ML
Work Timings: 1:00 PM – 10:00 PM IST (Mon – Fri)
Location: Remote
Qualifications & Requirements
Must-Have Skills:
Dataiku Expertise: Proven hands-on delivery with Dataiku, including Dataiku LLM Mesh (must speak to real production implementations, not just theoretical knowledge).
Snowflake: Solid hands-on experience integrating and querying Snowflake within AI pipelines.
GenAI Architecture: Solid grounding in LLMs, prompt engineering, RAG (Retrieval-Augmented Generation), and vector databases.
Agent Tooling: Demonstrated experience building agent tools, enabling autonomous decision-making, and setting up multi-agent collaboration models.
Nice-to-Have:
Domain Exposure: Experience in Pharma or Life Sciences (enterprise data, R&D, or drug-discovery use cases).

Work arrangement
Yes

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