Senior Azure AI Foundry Engineer

Interon IT Solutions LLC
Detroit, MI, United States
7 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
6 years minimum
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Application Performance Management Microsoft Azure Business Systems Cloud Computing Encodings Computer Programming Databases Information Engineering Data Retrieval Github
+29 more
Python (Programming Language) NoSQL Standard Sql Azure Data Lake Search Technologies Microsoft SharePoint Software Engineering SQL Databases Systems Integration Unstructured Data Data Logging Enterprise Software Applications Cloud Monitoring Retrieval-Augmented Generation Flask (Web Framework) Large Language Models Prompt Engineering Indexer Backend Git Fastapi Web Filtering Data Lakes AI Platforms Virtual Agents Restful APIs Serverless Computing Docker Key Vault

Job description

We are seeking an experienced Azure AI Foundry Engineer to design, develop, and deploy enterprise-grade generative AI solutions on the Microsoft Azure platform. The ideal candidate should have strong experience with Azure AI Foundry, Azure OpenAI, Retrieval-Augmented Generation, AI agents, Python, and cloud-native application development., Design and develop generative AI applications using Azure AI Foundry and Azure OpenAI. Build Retrieval-Augmented Generation solutions using Azure AI Search, vector databases, embeddings, and enterprise data sources. Develop AI agents capable of interacting with APIs, databases, documents, and other business systems. Design prompt workflows, system instructions, tool-calling processes, and multi-step agent workflows. Develop backend AI services and APIs using Python, FastAPI, Flask, or similar frameworks. Integrate structured and unstructured data from Azure Data Lake, Blob Storage, SQL databases, SharePoint, and enterprise applications. Implement document ingestion, chunking, embedding, indexing, retrieval, and response-generation pipelines. Evaluate AI applications for response accuracy, relevance, groundedness, safety, latency, and overall performance. Implement responsible AI controls, content filtering, prompt-injection protection, access controls, and data-security standards. Monitor AI applications using Azure Monitor, Application Insights, logging, tracing, and Foundry observability capabilities. Deploy and manage AI solutions using Azure Functions, Azure App Service, Azure Container Apps, AKS, or similar Azure services. Build automated CI/CD pipelines using Azure DevOps or GitHub Actions. Collaborate with data engineers, data scientists, architects, business analysts, and product teams. Troubleshoot issues related to model responses, data retrieval, integrations, application performance, and cloud deployment. Prepare technical design documents, architecture diagrams, deployment guides, and operational documentation.

Requirements

6+ years of overall software engineering, data engineering, cloud, or AI development experience. Strong hands-on experience with Azure AI Foundry or Microsoft Foundry. Experience with Azure OpenAI models, embeddings, chat completions, and model deployments. Strong experience developing RAG-based applications. Hands-on experience with Azure AI Search, vector search, semantic search, and hybrid search. Strong programming experience with Python. Experience developing REST APIs using FastAPI, Flask, or similar frameworks. Experience with prompt engineering, function calling, tool calling, and AI agent development. Understanding of LLM evaluation, hallucination reduction, groundedness, responsible AI, and content safety. Experience with Azure services such as Blob Storage, Data Lake, Key Vault, Functions, App Service, Container Apps, AKS, and Application Insights. Experience working with SQL, NoSQL, document databases, or vector databases. Experience with Git, Azure DevOps, GitHub Actions, Docker, and CI/CD processes.

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:13 min

Managing AI development with Azure AI Foundry

Ricardo Ricardo · World Congress 2025

6:21 min

Investigating push inefficiencies with upstream Git experts

Jonathan Creamer · Coffee With Developers

2:37 min

Comparing traditional SQL tables versus NoSQL non-tabular databases

Stanimira Vlaeva · JS Congress

2:07 min

Inspecting default bridge architectures and custom Docker networks

Oliver Seitz Oliver Seitz · World Congress 2025

39 sec

Orchestrating decisions using Azure AI Foundry

Alexandra Mihai Alexandra Mihai +2 · Europe 2026 Virtual

56 sec

Favorite git commands and the importance of patch commits

Eileen Uchitelle Eileen Uchitelle +1 · Coffee With Developers

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