We are seeking an AI Foundry Engineer to design, build, and operate AI-powered applications and agents on Microsoft Azure. In this role, you will use Azure AI Foundry to develop and deploy solutions such as conversational agents, retrieval-augmented generation (RAG), workflow automation, and enterprise AI integrations.

Key Responsibilities :

- Build AI solutions on Azure using Azure AI Foundry, Azure AI services, and modern application patterns (APIs, event-driven design, microservices).

- Design and implement agent-based solutions (tool/function calling, orchestration, guardrails, prompts, and evaluation) using Foundry capabilities and supporting Azure services.

- Develop RAG architectures : document ingestion, chunking/embedding strategies, semantic search, ranking, citations, and response grounding for enterprise knowledge.

- Integrate with enterprise systems such as APIs, databases, message queues, ITSM platforms, and line-of-business applications.

- Operationalize AI applications with telemetry, logging, prompt/version management, evaluation, and feedback loops to continuously improve quality and reliability.

Required Qualifications :

- 3+ years of professional software engineering experience building production systems.

- Hands-on development experience with Azure (e.g., App Services, Functions, AKS, Storage, Key Vault, Monitor/Log Analytics, API Management, networking basics).

- Demonstrated experience building AI-powered applications using one or more of the following :

1. Azure AI Foundry

2. Azure OpenAI / Azure AI services

3. Vector search / RAG patterns

- Strong programming skills in Python and/or C#.

- Experience building and consuming REST APIs, event-driven systems, and integrating with external services.

- Familiarity with DevOps practices : Git workflows, CI/CD, automated testing, and infrastructure-as-code.

- Strong problem-solving skills and ability to translate business requirements into scalable technical solutions.

Preferred Qualifications :

- Familiarity with prompt engineering, evaluation harnesses, red-teaming, and quality measurement for LLM outputs.

- Experience with Azure AI Search / vector search concepts and tuning relevance.

- Knowledge of containerization and orchestration for scalable deployments.