Design and implement enterprise AI solutions on Microsoft Azure, leveraging services such as Azure OpenAI Service, Azure Machine Learning, and Azure AI Search to support intelligent applications and automation.
Build and maintain scalable AI/ML pipelines and MLOps workflows using Azure-native tools (or equivalent), enabling reliable model training, deployment, monitoring, and lifecycle management.
Develop retrieval-augmented generation (RAG) solutions, integrating enterprise data sources with large language models to enable contextual knowledge assistants and intelligent automation.
Collaborate with business and technology stakeholders to translate business requirements into AI solution architectures, delivering measurable improvements in operational efficiency, decision intelligence, and customer experience.
Architect and develop AI-enabled applications, chatbots, and intelligent agents using Microsoft Copilot Studio, Azure Bot Service, and the Microsoft Power Platform ecosystem.
Implement secure and compliant AI deployments within Azure environments, incorporating private networking, identity-based access controls, and responsible AI governance practices.
Integrate AI capabilities with enterprise platforms such as ERP, analytics, and workflow systems, ensuring seamless data flow and scalable service integration.
Establish and enforce best practices for AI development, including prompt engineering, model evaluation, versioning, performance monitoring, and cost optimization.
Evaluate emerging AI frameworks, libraries, and tools to continuously improve solution performance and accelerate AI innovation within the enterprise.
Provide technical leadership and mentorship to development teams on modern AI development patterns, including LLM orchestration, vector search architectures, and enterprise AI integration.

Requirements

8+ years experience in Microsoft Azure AI ecosystem, including Azure OpenAI Service, Azure Machine Learning, Azure AI Search, and Azure data services.
Experience with LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and vector-based semantic search.
3+ years of experience with Large Language Models (LLM) such as OpenAI, Azure OpenAI, Hugging Face, Anthropic, etc.
5+ years of experience building production-grade AI assistants, chatbots, and intelligent agents using generative AI frameworks and orchestration tools.
Hands-on experience with Microsoft Copilot ecosystem, including Microsoft Copilot Studio and the Power Platform.
Proficiency in Python, SQL, and modern data engineering frameworks used in AI development pipelines.
MLOps principles, including model lifecycle management, CI/CD for ML, monitoring, and drift detection.
Experience integrating AI solutions with enterprise applications such as ERP, analytics platforms, and business process systems.
Strong understanding of security, compliance, and responsible AI governance, including data privacy and model transparency practices.
You will be required to work across engineering, data, and business teams to deliver scalable AI solutions.

Benefits

Comprehensive Health and Income Protection Benefits
401(k) Savings Plan
Paid Vacations for Qualifying Positions

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Microsoft AzureAzure OpenAI ServiceAzure Machine LearningAzure AI SearchPythonSQLMLOpsprompt engineeringretrieval-augmented generationLarge Language Models

Soft Skills

technical leadershipmentorshipcollaborationcommunicationproblem-solvingorganizational skillsstakeholder engagementdecision intelligenceoperational efficiencycustomer experience