Job Summary

Job Description: Azure AI Foundry – AI Developer (Agentic Systems)

Role Summary

We are seeking a hands-on AI Developer to build enterprise-grade multi-agent systems using Azure AI Foundry and Microsoft Agent Framework, with integration across cloud services, APIs, and DevOps pipelines. The role involves developing production-ready AI agents leveraging tools, memory, MCP integration, and workflow orchestration.

Key Responsibilities

Key Responsibilities

1. Develop AI applications using Azure AI Foundry (code-first approach)

• Build AI solutions using Python and/or TypeScript SDKs, integrating Foundry models, tools, and APIs.

2. Design and implement multi-agent systems using Microsoft Agent Framework (MAF)

• Build agents and multi-agent workflows (sequential, parallel, and collaborative orchestration) using Agent Framework capabilities.

3. Build SDK-agnostic agent architectures

• Develop solutions using MAF along with frameworks like LangGraph, AutoGen, CrewAI, ensuring portability and extensibility across ecosystems.

4. Implement orchestration and workflow execution logic

• Design graph/state-based workflows with task routing, retries, checkpointing, and human-in-the-loop approval flows.

5. Develop MCP-based tool integration layer

• Integrate external systems and APIs using Model Context Protocol (MCP) for standardized, secure tool access and orchestration.

6. Design agent memory and state management

• Implement short-term and long-term memory using Foundry memory stores for persistent context, personalization, and cross-session continuity.

7. Build and manage agent tools, skills, and capabilities

• Develop reusable tools, agent skills, and function interfaces (e.g., search, file access, APIs, automation) to support agent reasoning and action execution.

8. Develop RAG and knowledge grounding pipelines

• Integrate enterprise data sources using vector search and grounding (Azure AI Search, documents, APIs) to improve agent accuracy and contextual reasoning.

9. Implement observability, debugging, and telemetry

• Track agent workflows, tool usage, and decision flows using structured logging and monitoring for debugging and optimization.

10. Write scalable, production-grade AI systems (mandatory)

• Develop modular, secure backend services using Python/TypeScript, ensuring API design, performance, and integration with Azure services and DevOps pipelines.

Skill Requirements

Primary Skill: Azure AI Foundry, Microsoft Agent Framework (MAF), Python/TypeScript, Azure AI Search, Multi-Agent Systems

Relevant Experience: Minimum 2–4 years in AI/GenAI development, with hands-on experience in LLMs, RAG, or Agent-based frameworks

Other Requirements

• Mandatory Skills

  • Strong coding in Python and/or TypeScript
  • Hands-on experience with:
  • Azure AI Foundry / Azure OpenAI
  • Microsoft Agent Framework (MAF)
  • Multi-agent frameworks (LangGraph, AutoGen, CrewAI)
  • Experience with:
  • MCP / API integrations
  • Memory and agent state management
  • RAG (vector search, embeddings)

   

  One-line Hiring Filter

  Must have hands-on experience building production AI systems using Python/TypeScript, including multi-agent orchestration, MCP/tool integrations, memory design, RAG pipelines, and API/tool integrations and workflow-based agent execution using Azure AI Foundry or similar platforms.