AI Architect - RAG & Agentic AI

Job Summary

We are looking for a highly skilled, hands-on AI Architect with deep expertise in Agentic AI, Multi-Agent Systems, RAG architecture, and enterprise AI solutions.

The ideal candidate should have strong Python development skills, a solid foundation in data architecture, and proven experience building and deploying AI agents from scratch.

They also should have Snowflake and Databricks experience.

Key Responsibilities

• Design and build enterprise-grade Agentic AI solutions, including conversational AI, autonomous agents, and multi-agent systems.
• Architect and implement advanced RAG pipelines, vector search, embeddings, retrieval strategies, and context management.
• Develop AI agents from scratch using Python, LangGraph, LangChain, Claude Agent SDK, or similar frameworks.
• Design agent orchestration, agent-to-agent communication, tool integrations, and intelligent workflows.
• Own end-to-end AI solution architecture, from design and development to production deployment.
• Design data pipelines and integrate enterprise data sources using Azure, Databricks, Snowflake, and related technologies.
• Ensure data quality, accessibility, security, governance, and reliability for AI applications.
• Lead and mentor engineers while remaining actively involved in hands-on development.
• Collaborate with enterprise architects, advisory teams, and client stakeholders.

Required Skills

• Strong hands-on experience in Agentic AI, Multi-Agent Systems, and RAG architecture.
• Expert-level Python programming and AI application development.
• Experience building AI agents and integrating existing LLMs such as Claude, OpenAI, or Azure OpenAI.
• Strong understanding of enterprise architecture, data engineering, ETL/ELT pipelines, and cloud platforms.
• Experience with agent frameworks, vector databases, API integrations, and AI orchestration.
• Strong technical leadership, problem-solving, and communication skills.
• Experience delivering enterprise AI solutions in a consulting or services environment is preferred.

Key Expectation

We need a hands-on AI Architect who has personally designed, coded, and deployed AI agents and multi-agent solutions—not someone with only theoretical knowledge or high-level architecture experience.

Building new LLMs from scratch is not required.