Note: The job is a remote job and is open to candidates in USA. GovCIO is seeking a highly experienced technical leader to advance secure enterprise AI capabilities for a federal customer. The Senior Azure AI Solutions Architect / Engineer will architect, develop, integrate, and deploy Generative AI, intelligent document processing, enterprise search, and Retrieval-Augmented Generation solutions using Microsoft Azure AI services.
Responsibilities
- Lead the architecture, design, development, and implementation of enterprise Generative AI solutions using the Microsoft Azure AI ecosystem
- Design and implement solutions using Microsoft Foundry, Azure OpenAI/model services, Azure AI Search, Azure AI Document Intelligence, and related Azure capabilities
- Architect and implement Retrieval-Augmented Generation (RAG) solutions over enterprise structured and unstructured data
- Develop AI-assisted enterprise search capabilities capable of identifying relevant documents, pages, data elements, and supporting evidence across large document repositories
- Develop capabilities for natural-language question answering, document summarization, information extraction, structured output generation, and AI-assisted research
- Design and implement semantic, vector, hybrid, and agentic retrieval approaches as appropriate for specific business requirements
- Develop secure integration patterns between Azure AI services and existing enterprise applications, APIs, databases, and document repositories
- Integrate AI functionality into existing enterprise applications through REST APIs, SDKs, Java services, and other approved integration patterns
- Evaluate and implement Azure AI Document Intelligence capabilities for document classification, metadata/data extraction, confidence scoring, and exception handling
- Design AI agents and orchestration workflows using Microsoft Foundry capabilities when appropriate
- Partner with existing application, IBM FileNet and IBM DataCap technical teams to introduce AI capabilities while leveraging existing enterprise platforms and investments
- Design solutions that preserve application-level authorization and ensure users only receive AI-generated information derived from data they are authorized to access
- Implement appropriate Azure identity, access management, secrets management, networking, logging, monitoring, and security controls
- Establish AI evaluation and testing frameworks measuring retrieval accuracy, extraction accuracy, groundedness, hallucination rates, confidence, latency, performance, and business outcomes
- Develop and execute technical proofs of concept and MVPs and transition successful capabilities into secure, scalable production implementations
- Work with business and technical stakeholders to translate business processes and pain points into actionable AI solutions
- Evaluate alternative AI technologies and integration approaches and provide technical recommendations based on feasibility, security, cost, scalability, and business value
- Establish reusable architecture patterns, development standards, and technical documentation for future enterprise AI implementations
- Mentor existing architects and developers on Azure AI, RAG, LLM integration, prompt engineering, evaluation, and responsible AI development
- Provide hands-on knowledge transfer so that successful AI capabilities can ultimately be maintained and expanded by the existing technical organization
Skills
- 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
- Clearance Level: Public Trust
- 8+ years of progressive experiencedesigning, developing, and implementing enterprise software, cloud, or data solutions
- 5+ years of experienceserving in senior engineering, technical architecture, cloud architecture, or comparable solution-design roles
- 3+ years of hands-on experiencedesigning or implementing AI/ML solutions
- 2+ years of recent hands-on experiencedesigning and implementing Generative AI, LLM, and/or RAG-based applications
- Demonstrated hands-on experience with theMicrosoft Azure AI ecosystem, including Microsoft Foundry/Azure AI Foundry and Azure-hosted foundation models
- Demonstrated experience designing and implementingRAG architecturesusing enterprise data
- Hands-on experience withAzure AI Searchor comparable enterprise semantic/vector search technologies
- Strong 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 secureREST API and SDK-based integrations
- Experience withPython and/or Javafor enterprise AI/application development
- Experience with Microsoft Azure architecture, includingEntra ID, RBAC, managed identities, Key Vault, networking, storage, monitoring, and logging
- Demonstrated ability to design solutions involving sensitive or restricted enterprise information with appropriate data isolation and authorization controls
- Demonstrated experience takingat 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
- Demonstrated ability to communicate complex AI architecture and technical concepts to both technical and non-technical stakeholders
- Experience mentoring developers and transferring technical knowledge to existing engineering teams
- Candidates located in the DC area are highly preferred
- Hands-on experience with Azure AI Document Intelligence, including document classification, custom extraction, structured data extraction, confidence scoring, and exception processing
- Experience buildingenterprise document intelligence, document search, or knowledge retrieval solutionsinvolving large volumes of unstructured content
- Experience integrating AI solutions with enterprise content-management systems such asIBM FileNet
- Experience withIBM DataCapor comparable enterprise document capture and processing platforms
- Experience integrating AI functionality into existingJava-based enterprise applications
- Experience with Microsoft Foundry Agent Service and agentic AI architectures
- Experience withMicrosoft Copilot Studio, including agents, connectors, actions, and enterprise workflow integration
- Experience with Azure DevOps, Git, CI/CD, Infrastructure as Code, and DevSecOps practices for AI-enabled applications
- Experience implementing AI evaluation frameworks and automated testing for production LLM applications
- Experience with document-level/page-level citations, source attribution, and explainable/traceable AI responses
- Experience implementing human-in-the-loop workflows and confidence-based exception routing
- Knowledge of responsible AI principles, model governance, data privacy, and AI risk management
- Experience working with PII, financial, benefits, healthcare, or other regulated/sensitive information
- Experience delivering solutions withinfederal government environments, including familiarity with FedRAMP, NIST controls, FISMA, ATO processes, and federal security requirements
- Experience evaluating AI platforms, models, and services based on cost, performance, security, accuracy, and operational suitability
- Experience with IBM watsonx or other enterprise AI platforms is beneficial but not required
Benefits
- The position is remote and supports a federal customer in the Washington, D.C. metropolitan area.
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