Own architecture and design of production grade Data & AI platforms spanning cloud infrastructure (Azure), data platforms, ML/LLM systems, and agentic workflows
Job Summary
Own architecture and design of production grade Data & AI platforms spanning cloud infrastructure (Azure), data platforms, ML/LLM systems, and agentic workflows.
Architect and drive AI agents using LangGraph, LangChain Expression Language (LCEL), Semantic Kernel, or similar frameworks, emphasizing context engineering, tool routing, memory strategies, guardrails, and deterministic workflows over prompt hacks.
Lead production deployments using Azure ML, Databricks, AKS, MLflow, CI/CD, feature stores, monitoring, logging, and incident ready observability for both ML models and AI agents.
Matching Summary
Own architecture and design of production grade Data & AI platforms spanning cloud infrastructure (Azure), data platforms, ML/LLM systems, and agentic workflows.
Skills & Requirements
Must-have
End-to-end architecture ownership
Agentic AI systems with LangGraph/LCEL
Context and retrieval engineering
Model and agent evaluation frameworks
Data mesh aligned platforms
Production deployment and operations on Azure
Nice-to-have
Pragmatic mindset focused on production
Influencing technical direction
Stakeholder management
Key Requirements
11-12 years building Data & AI systems
Proven production deployments of ML and agent based AI systems
Strong hands-on experience with Python
Experience with Azure cloud native architectures
Expertise in agent design patterns
Solid grounding in data architecture and databases