Senior Azure AI Solutions Architect / Engineer

Role Description

GovCIO is currently hiring for a highly experienced, hands-on Senior Azure AI Solutions Architect / Engineer to lead the architecture, development, and implementation of enterprise Generative AI and intelligent document solutions within a complex federal application environment. This individual will serve as a technical leader for the adoption of Microsoft Azure AI capabilities, working alongside existing application architects, developers, infrastructure teams, and subject matter experts to introduce secure, scalable AI capabilities into established enterprise systems.

Initial efforts will focus on:

• AI-assisted document intelligence
• Enterprise search and retrieval
• Retrieval-Augmented Generation (RAG)
• Document summarization
• Structured data extraction
• Document classification
• AI-assisted business process automation

The successful candidate must be equally comfortable designing the architecture and building the solution. This is not solely an advisory or strategy position. The individual will be expected to:

• Configure Azure AI services
• Develop prototypes and production solutions
• Integrate with existing applications and data repositories
• Troubleshoot technical challenges
• Establish AI development patterns
• Transfer knowledge to existing technical teams

The position is remote and supports a federal customer in the Washington, D.C. metropolitan area.

Qualifications

• 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

Requirements

• 8+ years of progressive experience designing, developing, and implementing enterprise software, cloud, or data solutions.
• 5+ years of experience serving 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.
• Demonstrated hands-on experience with the Microsoft Azure AI ecosystem, including Microsoft Foundry/Azure AI Foundry and Azure-hosted foundation models.
• Demonstrated experience designing and implementing RAG architectures using enterprise data.
• Hands-on experience with Azure AI Search or 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 secure REST API and SDK-based integrations.
• Experience with Python and/or Java for enterprise AI/application development.
• Experience with Microsoft Azure architecture, including Entra 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 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.
• 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.

Preferred Skills & Experience

• 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 building enterprise document intelligence, document search, or knowledge retrieval solutions involving large volumes of unstructured content.
• Experience integrating AI solutions with enterprise content-management systems such as IBM FileNet.
• Experience with IBM DataCap or comparable enterprise document capture and processing platforms.
• Experience integrating AI functionality into existing Java-based enterprise applications.
• Experience with Microsoft Foundry Agent Service and agentic AI architectures.
• Experience with Microsoft 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 within federal 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.

Posted Salary Range

USD $180,000.00 - USD $220,000.00 /Yr.