Description

You will architect scalable, high-performance cloud data platforms and AI/ML solutions across AWS, Azure, and Google Cloud.

This role is hybrid.

Responsibilities

• Design and implement modern data stack solutions using Snowflake and Databricks for real-time and batch workloads.
• Architect GenAI, RAG, and Agentic AI solutions, including vector databases and semantic search frameworks.
• Operationalize MLOps and LLMOps pipelines for scalable model deployment, monitoring, and lifecycle management.
• Establish enterprise-wide data governance, security, and compliance frameworks, including MDM and AI governance controls.
• Lead architectural decisions across multiple programs and mentor senior engineers on best practices.

Required Skills

• 10+ years of experience in data architecture and engineering.
• Deep expertise in cloud platforms: AWS, Azure, or Google Cloud.
• Hands-on experience with Snowflake and Databricks.
• Strong background in AI/ML architecture, specifically GenAI and RAG.
• Knowledge of vector databases (e.g., Pinecone, FAISS) and semantic search.
• Experience with MLOps/LLMOps tools and frameworks.
• Understanding of data governance, privacy, compliance, and Master Data Management (MDM).
• Bachelor's degree or equivalent experience.

Preferred Skills

• Experience in BFSI or regulated industries.
• Exposure to large-scale AI transformation initiatives.
• Relevant cloud or data platform certifications.

Key Skills

Education

Any Gradute