We are seeking an AI 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 up-to-date 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
4+ years of qualified 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) and Amazon Bedrock.
Demonstrated experience building AI-powered applications using one or more of the following:
Azure AI Foundry
Azure OpenAI / Azure AI services
Vector search / RAG patterns
Solid 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.
Robust 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.

Core Technologies
Azure AI Foundry, Azure OpenAI / Azure AI services
Amazon Bedrock
Azure Functions / App Service
Azure AI Search (vector + semantic), Storage Accounts, Cosmos DB/SQL
Azure DevOps

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