ResponsibilitiesPosition Overview:Looking for your next challenge? Enjoy solving complex business problems with today's latest technologies? REI Systems (REI) is looking for innovative Entreprise Solutions Architect to craft compelling and compliant cloud-based solutions for REI's clients. Working with REI's FDA Account Management and REI's Leadership, successful candidates will support REI's growth strategy, application modernization endeavors, while ensuring solution excellence for our customers. The position enables REI to provide best-in-class thought-leadership and support to our Accounts. It also contributes toward REI's long-term strategy to organically acquire and retain customers and talent while expanding and deepening our portfolio of offerings.
REI Systems is seeking an experienced
AI Visionary / Architect to provide strategic and technical leadership in the adoption, architecture, and implementation of Artificial Intelligence across complex enterprise and Federal environments. This individual will help define the AI vision, identify high-value opportunities, establish reusable AI architecture patterns, and guide the delivery of secure, scalable, responsible, and mission-aligned AI solutions.
The ideal candidate combines deep technical expertise in Generative AI, machine learning, intelligent automation, cloud architecture, and enterprise integration with the ability to engage executives, business leaders, program teams, and technical stakeholders. This role will help customers move from AI experimentation to sustainable enterprise adoption.
Responsibilities- Define and communicate an enterprise AI vision, strategy, roadmap, and reference architecture aligned with customer mission and business priorities.
- Identify and evaluate high-value AI, Generative AI, machine learning, agentic AI, and intelligent automation use cases.
- Design scalable AI architectures incorporating Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, machine learning, APIs, data platforms, and cloud-native services.
- Establish reusable AI architecture patterns, frameworks, accelerators, and implementation standards.
- Provide technical leadership for AI pilots, proofs of concept, prototypes, and enterprise-scale production implementations.
- Evaluate commercial, open-source, and cloud-native AI technologies and recommend appropriate solutions based on mission, security, scalability, cost, and performance requirements.
- Architect secure AI solutions across AWS, Azure, and/or other approved Federal cloud environments.
- Define approaches for model selection, model hosting, prompt engineering, embeddings, vector databases, grounding, orchestration, evaluation, and monitoring.
- Develop strategies for enterprise AI agents and multi-agent systems that securely integrate with organizational applications, data, APIs, and workflows.
- Partner with data engineering and analytics teams to ensure AI solutions have access to trusted, governed, and high-quality enterprise data.
- Establish AI governance practices addressing security, privacy, explainability, transparency, model risk, bias, data protection, human oversight, and responsible AI.
- Ensure AI architectures comply with applicable Federal security, privacy, accessibility, records management, and responsible AI requirements.
- Collaborate with cybersecurity teams to address AI-specific risks including prompt injection, data leakage, model manipulation, access control, and adversarial threats.
- Define AI solution evaluation frameworks including accuracy, relevance, hallucination reduction, performance, scalability, security, and mission effectiveness.
- Provide architectural guidance throughout the full solution lifecycle, from discovery and design through implementation, testing, deployment, and optimization.
- Work closely with Enterprise Architects, Chief Architects, Solution Architects, Product Owners, engineers, data scientists, and program leadership.
- Facilitate architecture workshops, AI discovery sessions, technical reviews, and executive-level discussions.
- Translate complex AI concepts into practical recommendations for both technical and non-technical stakeholders.
- Support proposal development, solutioning, technical demonstrations, white papers, and other business development activities related to AI and emerging technologies.
- Monitor developments across the AI ecosystem and recommend emerging technologies that may provide meaningful customer or mission value.
- Mentor technical teams and help strengthen AI engineering and architecture capabilities across the organization.
Qualifications- 12+ years of experience in software engineering, solution architecture, enterprise architecture, cloud architecture, data, or related technology disciplines.
- Significant hands-on or architecture-level experience with Artificial Intelligence, machine learning, Generative AI, or advanced analytics.
- Demonstrated experience designing enterprise AI solutions using LLMs, RAG architectures, AI agents, APIs, vector databases, and cloud AI services.
- Strong understanding of AI architecture, software architecture, data architecture, cloud computing, API integration, and cybersecurity.
- Experience with AWS and/or Microsoft Azure AI and cloud services.
- Experience translating organizational objectives into technical strategies and enterprise architecture.
- Strong executive communication, presentation, facilitation, and technical storytelling skills.
- Experience leading architecture discussions involving multiple technical disciplines and stakeholder groups.
- Ability to obtain and maintain a Federal Public Trust or other required government clearance.
Preferred Qualifications- Experience supporting Federal Government or highly regulated environments.
- Experience with AWS Bedrock, Amazon SageMaker, Azure OpenAI, Azure AI Foundry, Databricks, Snowflake, or comparable AI/data platforms.
- Experience with LangChain, LangGraph, Semantic Kernel, LlamaIndex, or similar AI orchestration frameworks.
- Familiarity with MLOps, LLMOps, DevSecOps, CI/CD, containerization, Kubernetes, infrastructure as code, and automated AI evaluation.
- Knowledge of NIST AI Risk Management Framework, Federal AI governance requirements, and responsible AI practices.
- Experience establishing AI Centers of Excellence, governance boards, architecture standards, or reusable enterprise AI platforms.
- Cloud, architecture, security, data, or AI-related professional certifications.
- Prior experience supporting HHS, FDA, DHS, CMS, HRSA, or other Federal civilian agencies is a plus.
Educational Qualifications:Bachelor's degree in Information Technology, Cybersecurity, Operations Management, or related field.
Clearance: Eligible to obtain a public trust clearance.
Location: Hybrid (2 days per week or as needed in the REI Sterling Office)
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