Description

Design and build scalable, production-grade AI systems with a focus on agentic architectures and distributed systems.

This role is on-site.

Responsibilities

• Develop and maintain Agentic Layer A2A frameworks and implement the MCP Protocol.
• Design and optimize vector embeddings, prompt engineering, and context engineering pipelines.
• Deploy and manage cloud-native solutions using Azure Functions and Azure Container Apps.
• Architect scalable data layers using Azure AI Search, Redis, and Cosmos DB.

Required Skills

• 12+ years of experience in Data Science.
• 6+ years in AI/ML engineering, specifically with vector embeddings, prompt engineering, and context engineering.
• 6+ years of hands-on programming in at least two of: Python, Java, or Go.
• 6+ years of experience deploying solutions on Azure Cloud.
• 6+ years of experience with databases including Azure AI Search, Redis, and Cosmos DB (Blob Storage/Iceberg is a plus).
• Proven ability to design and manage cloud-native architecture, focusing on scalability and performance optimization.

Key Skills

Education

Bachelor's degree