Data Scientist - R01569584 at Brillio (Pune, India)
Brillio· Pune, India·
Role details
Work type
Hybrid
Job description
Data Scientist – Snowflake + Agentic AI / Cortex AI
Primary Skills
We are looking for an experienced Data Scientist with strong expertise in Snowflake and hands-on exposure to Agentic AI / Snowflake Cortex AI to join our team.
🔹 Experience: 5+ years 🔹 Location: Bangalore / Hyderabad / Pune 🔹 Notice Period: Immediate to 30 days preferred
Key Skills
- Strong experience in Data Science, Python & SQL
- Hands-on experience with Snowflake
- Experience with Snowpark and Snowflake data platforms
- Exposure to Snowflake Cortex AI – Cortex Analyst, Cortex Search, Cortex Agents, etc.
- Strong understanding of Generative AI, LLMs, RAG and Prompt Engineering
- Experience with Agentic AI / AI Agents
- Knowledge of Vector Search, Embeddings and LLM integration
- Experience with ML algorithms, model development and deployment
- Experience integrating AI/ML solutions with enterprise data platforms
Job requirements
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What We’re Looking For
Candidates who have worked on production-grade Data Science + GenAI/Agentic AI solutions and can leverage Snowflake/Cortex capabilities to build intelligent data-driven applications.
Why work at Brillio
- Culture: Rated 4.0/5.0 on Glassdoor (2,264 reviews) and 4.0/5.0 on LinkedIn; 80% would recommend to a friend; Great Place to Work® certified in the USA.
- Work environment: Engineers get meaningful ownership within clear guardrails – autonomy to make architecture and trade-off calls on their workstreams.
- Learning & growth: Brillio Academy, hackathons, personalized career development framework; exposure to cutting-edge GenAI and agentic AI projects.
- Remote / hybrid / office: Not explicitly stated, but global delivery locations suggest a mix of on-site and remote (roles posted across multiple countries).
- Benefits: “BYou” wellness program built on four pillars of wellness – personal and professional well-being and development.
- Interview process: Focus on software fundamentals, LLMs, RAG, agents, evaluation, and a design or debugging exercise; candidates should be ready to walk through a real system they shipped.