Senior Azure AI Solutions Architect - Engineer

GovCIO

. Lead the architecture, design, development, and implementation of enterprise Generative AI solutions using Microsoft Azure AI.

Posted 11/2/2026full-timeRemote • United StatesSenior💰 $180,000 - $220,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and implementing Generative AI solutions using Microsoft Azure AI, with a strong focus on secure integrations, AI evaluation frameworks, and mentoring technical teams. Proficient in translating complex business processes into actionable AI strategies while ensuring compliance with security and regulatory standards.

Highest-signal resume keywords

Microsoft Azure AIGenerative AI SolutionsRAG Architecture DesignAI Evaluation FrameworksSecure REST API Integrations

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

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

Hard Skills

PythonJavaAI/ML Solution DesignEnterprise Software DevelopmentCloud ArchitectureData Solutions ImplementationPrompt EngineeringVector Search TechnologiesDocument Processing StrategiesAI Orchestration

Soft Skills

MentoringCommunicationCollaboration

Tools & Technologies

Microsoft FoundryAzure AI SearchAzure AI Document IntelligenceIBM FileNetIBM DataCapAzure DevOpsGitCI/CDInfrastructure as CodeDevSecOps

Certifications & Qualifications

Public Trust Clearance

Industry Keywords

Enterprise AIRegulated InformationFederal Government EnvironmentsFedRAMPNISTFISMAATO ProcessesResponsible AIHuman-in-the-Loop WorkflowsCitations/Source Attribution

Tech Stack

Tools & technologies

AzureCloudJavaPythonVault

About the role

Key responsibilities & impact

Lead the architecture, design, development, and implementation of enterprise Generative AI solutions using Microsoft Azure AI.
Design and implement solutions with Microsoft Foundry, Azure OpenAI/model services, Azure AI Search, Azure AI Document Intelligence, and related Azure capabilities.
Architect and implement RAG solutions over structured and unstructured enterprise data.
Develop enterprise search, natural-language question answering, document summarization, information extraction, structured output, and AI-assisted research capabilities.
Design semantic, vector, hybrid, and agentic retrieval approaches.
Develop secure integrations between Azure AI services and enterprise applications, APIs, databases, and document repositories.
Integrate AI functionality through REST APIs, SDKs, Java services, and approved integration patterns.
Evaluate Azure AI Document Intelligence for classification, extraction, confidence scoring, and exception handling.
Design AI agents and orchestration workflows using Microsoft Foundry.
Partner with application, IBM FileNet, and IBM DataCap teams to introduce AI capabilities.
Preserve application-level authorization and ensure AI responses derive only from authorized data.
Implement identity, access management, secrets management, networking, logging, monitoring, and security controls.
Establish AI evaluation and testing frameworks for accuracy, groundedness, hallucination, confidence, latency, performance, and business outcomes.
Develop proofs of concept and MVPs and transition successful capabilities into secure, scalable production implementations.
Translate business processes and pain points into actionable AI solutions.
Evaluate AI technologies and integration approaches and provide recommendations.
Establish reusable architecture patterns, development standards, and technical documentation.
Mentor architects and developers on Azure AI, RAG, LLM integration, prompt engineering, evaluation, and responsible AI.
Transfer knowledge so existing technical teams can maintain and expand AI capabilities.

Requirements

What you’ll need

Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Science, Artificial Intelligence, Engineering, or a related technical discipline with 12 years (or commensurate experience.
Public Trust clearance.
8+ years of progressive experience designing, developing, and implementing enterprise software, cloud, or data solutions.
5+ years of experience in senior engineering, technical architecture, cloud architecture, or comparable solution-design roles.
3+ years of hands-on experience designing or implementing AI/ML solutions.
2+ years of recent hands-on experience designing and implementing Generative AI, LLM, and/or RAG-based applications.
Hands-on experience with Microsoft Azure AI, including Microsoft Foundry/Azure AI Foundry and Azure-hosted foundation models.
Experience designing and implementing RAG architectures using enterprise data.
Experience with Azure AI Search or comparable enterprise semantic/vector search technologies.
Understanding of vector embeddings and vector databases/search, semantic and hybrid search, chunking and document-processing strategies, prompt engineering and context management, grounding and citation/source attribution, LLM orchestration, AI evaluation, and hallucination mitigation.
Experience integrating LLMs and AI services with enterprise data sources and applications.
Experience designing and implementing secure REST API and SDK-based integrations.
Experience with Python and/or Java.
Experience with Microsoft Azure architecture, including Entra ID, RBAC, managed identities, Key Vault, networking, storage, monitoring, and logging.
Ability to design solutions involving sensitive or restricted enterprise information with appropriate data isolation and authorization controls.
Experience taking at least one enterprise AI/ML solution from architecture or proof-of-concept through production deployment.
Experience establishing technical architecture while remaining directly involved in hands-on development and troubleshooting.
Ability to communicate complex AI architecture and technical concepts to technical and non-technical stakeholders.
Experience mentoring developers and transferring technical knowledge to engineering teams.
Candidates located in the DC area are highly preferred.
Preferred experience with Azure AI Document Intelligence, enterprise document intelligence/search/knowledge retrieval, IBM FileNet, IBM DataCap, Java enterprise applications, Microsoft Foundry Agent Service, Copilot Studio, Azure DevOps, Git, CI/CD, Infrastructure as Code, DevSecOps, AI evaluation frameworks, citations/source attribution, human-in-the-loop workflows, responsible AI, regulated information, federal government environments, FedRAMP, NIST, FISMA, ATO processes, AI platform evaluation, and IBM watsonx.