Senior Azure AI Solutions Architect - Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee the architecture, design, development, and deployment of enterprise Generative AI solutions utilizing Microsoft Azure AI.

• Create and implement solutions using Microsoft Foundry, Azure OpenAI/model services, Azure AI Search, Azure AI Document Intelligence, and other associated Azure functionalities.

• Architect and execute RAG solutions for both structured and unstructured enterprise data.

• Develop capabilities for enterprise search, natural-language question answering, document summarization, information extraction, structured output, and AI-assisted research.

• Design retrieval strategies including semantic, vector, hybrid, and agentic approaches.

• Create secure integrations between Azure AI services and enterprise applications, APIs, databases, and document repositories.

• Incorporate AI functionality through REST APIs, SDKs, Java services, and recognized integration methodologies.

• Assess Azure AI Document Intelligence for tasks such as classification, extraction, confidence scoring, and exception management.

• Design AI agents and orchestration workflows utilizing Microsoft Foundry.

• Collaborate with application teams, IBM FileNet, and IBM DataCap to introduce AI functionalities.

• Maintain application-level authorization and ensure AI responses are derived solely from permitted data.

• Implement identity, access management, secrets management, networking, logging, monitoring, and security protocols.

• Create AI evaluation and testing frameworks focused on accuracy, groundedness, hallucination, confidence, latency, performance, and business outcomes.

• Develop proofs of concept and MVPs, transitioning successful capabilities into secure, scalable production implementations.

• Convert business processes and challenges into actionable AI solutions.

• Analyze AI technologies and integration methods, providing informed recommendations.

• Establish reusable architectural patterns, development standards, and comprehensive technical documentation.

• Mentor architects and developers on Azure AI, RAG, LLM integration, prompt engineering, evaluation, and responsible AI practices.

• Facilitate the transfer of knowledge to ensure existing technical teams can maintain and expand AI capabilities.

⛳️ Requirements

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Science, Artificial Intelligence, Engineering, or a related technical field, along with 12 years of experience (or equivalent).

• Possession of Public Trust clearance.

• Over 8 years of progressive experience in the design, development, and implementation of enterprise software, cloud, or data solutions.

• More than 5 years of experience in senior engineering, technical architecture, cloud architecture, or similar solution-design roles.

• At least 3 years of practical experience in designing or implementing AI/ML solutions.

• Minimum of 2 years of recent hands-on experience in designing and implementing Generative AI, LLM, and/or RAG-based applications.

• Practical experience with Microsoft Azure AI, including Microsoft Foundry/Azure AI Foundry and Azure-hosted foundational models.

• Experience in designing and implementing RAG architectures utilizing enterprise data.

• Familiarity with Azure AI Search or equivalent enterprise semantic/vector search technologies.

• Knowledge of vector embeddings, 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 in integrating LLMs and AI services with enterprise data sources and applications.

• Background in designing and implementing secure REST API and SDK-based integrations.

• Proficiency in Python and/or Java.

• Familiarity 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 necessary data isolation and authorization controls.

• Experience in taking at least one enterprise AI/ML solution from architecture or proof-of-concept through to production deployment.

• Proven experience in establishing technical architecture while remaining actively involved in hands-on development and troubleshooting.

• Capability to convey intricate AI architecture and technical concepts to both technical and non-technical stakeholders.

• Experience mentoring developers and disseminating technical knowledge to engineering teams.

• Candidates located in the DC area are highly preferred.

• Preferred experience includes 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.

🏝️ Benefits

• Comprehensive health and wellness benefits.

• Retirement savings plans with employer matching.

• Opportunities for professional development and continuing education.

• Flexible work arrangements and a supportive work environment.