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# Cyber Systems Engineer/AI Governance Lead/Solutions Architect

- **Company:** LMI
- **Location:** Tysons, VA, United States
- **Experience:** Expert
- **Salary:** $185,000.0 - $225,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Health Informatics, Software as a Service, Cloud Computing, Cloud Engineering, Cyber Security, Information Systems, Data Integration, Decision Support Systems, Interoperability, Zero Trust Network Access, Data Logging, Technical Debt, Generative AI, Togaf, AI Platforms, Information Technology, Low-code, Data Management
- **Published:** September 30, 2026
- **Apply:** https://careers-lmi.icims.com/jobs/14652/cyber-systems-engineer-ai-governance-lead-solutions-architect/job?mode=apply&apply=yes&in_iframe=1&hashed=-336058770

## About the Role

This position requires a senior practitioner who can move between executive-level tradeoffs and detailed technical questions, challenge assumptions, identify material AI or technology risk, right-size governance to the use case, and guide teams toward reusable patterns without becoming the default day-to-day architect or developer.

The ideal candidate combines enterprise and solution architecture depth with strong technology-risk judgment, responsible-AI fluency, and the communication skills to explain complex technical and governance issues to engineers, cybersecurity/privacy specialists, data teams, clinicians, program leaders, and executives., * Bachelor's degree in computer science, information systems, engineering, cybersecurity, data science, public policy, risk management, or a related field; equivalent professional experience may be considered.

 * 10+ years of progressive experience across enterprise/solution architecture, systems design, cybersecurity or technology risk, technical consulting, AI governance, or related modernization work.
 * Demonstrated solution-architecture depth across applications, APIs/integration, data, cloud/platform, identity, security, networking, and operational support, including lifecycle tradeoffs.
 * Demonstrated experience operationalizing technology or AI governance through risk tiers, review criteria, control libraries, decision records, approval processes, or lifecycle governance.
 * Strong working knowledge of AI/ML and generative-AI lifecycle concepts, data quality, model/product limitations, human oversight, transparency, privacy, security, and post-deployment monitoring.
 * Proven ability to translate policy, regulatory guidance, enterprise standards, and risk requirements into practical technical controls and architecture decisions.
 * Experience assessing cloud, SaaS, low-code, custom-development, integration, and data-platform options for interoperability, supportability, security, maintainability, and enterprise fit.
 * Experience in federal or regulated environments where identity, authorization, records, accessibility, privacy, security, and operational approval constraints materially affect technical design.
 * Strong executive and technical communication skills, including architecture diagrams, option analysis, decision records, risk narratives, and concise documentation of assumptions and limitations.
 * Recommended certification: TOGAF, Azure Solutions Architect Expert, AWS Solutions Architect Professional, or comparable architecture/cloud credential.
 * Ability to satisfy VA personnel vetting and applicable security, privacy, records, training, and data-handling requirements.

Desired Qualifications

 * 12+ years in federal or regulated enterprise architecture, technology/AI governance, cybersecurity risk, or large-scale modernization.
 * Prior VA, VHA, VA OIT, federal health, or other large federal-enterprise experience with shared platforms, data, identity, and approval processes.
 * Experience with NIST AI risk-management concepts, federal responsible-AI practices, model risk management, algorithmic impact assessment, AI assurance, validation, or high-impact automated decision support.
 * Experience establishing reusable architecture standards, reference patterns, shared controls, or technical governance practices across a portfolio.
 * Experience with Zero Trust, cloud-native architecture, enterprise identity, APIs, data integration, Microsoft Azure/Power Platform, observability, secure software delivery, or AI services in regulated environments.
 * Additional IAPP AIGP, CISSP/CCSP, CISM/CRISC, privacy, or advanced cloud/security architecture certifications are preferred.

## Description

* Lead independent solution-architecture and AI/technology-governance review for complex VA modernization initiatives.
 * Evaluate solution options for enterprise fit, reuse, integration, maintainability, supportability, scalability, security, data dependencies, and lifecycle cost.
 * Establish risk-tiering and review criteria so governance depth is proportionate to intended use, affected users, data sensitivity, autonomy, operational impact, and potential harm.
 * Translate VA and federal policy, responsible-AI expectations, cybersecurity/privacy requirements, and enterprise standards into practical architecture requirements, controls, and decision criteria.
 * Review higher-risk AI, data, clinical, identity, automation, and workflow use cases and identify when additional validation, formal escalation, or executive decision is required.
 * Shape major technical tradeoffs across applications, APIs/integration, data, cloud/platform, identity, low-code, automation, and AI-enabled solution patterns.
 * Define non-functional requirements covering interoperability, data protection, identity, logging/auditability, observability, resilience, accessibility, human oversight, monitoring, and operational support.
 * Maintain architecture decision records, governance assessments, assumptions, approvals, exceptions, risk treatments, accountable owners, and unresolved questions for traceability.
 * Develop reusable reference architectures, governance checklists, technical patterns, review templates, and decision guidance that accelerate future VA initiatives.
 * Facilitate architecture and governance reviews that produce clear decisions, owners, actions, and escalation paths rather than unresolved technical debate.
 * Partner with cybersecurity/privacy, data, clinical informatics, HCD, platform, engineering, testing, and program leadership to resolve cross-cutting constraints and right-size controls.
 * Assess technical debt, vendor lock-in, sustainment, operational ownership, model/system change, and post-deployment monitoring before major decisions are finalized.
 * Support implementation and readiness reviews to confirm material architecture and governance assumptions remain valid as solutions move from design into pilot, deployment, or scale.
 * Track recurring architecture and governance findings and recommend shared services, reference patterns, standards, or portfolio-level improvements that reduce one-off solution design.


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