Senior AI Solutions Architect

Cynet Systems • Lehi, UT

4d

About The Position

Lead hands-on solution architecture for Engineering Services (ES) platforms and managed business services. Partner with service owners and customers to identify where AI or simpler automation can add value, then guide the design, engineering, and reliable operation of those capabilities.

The role works with ES service owners, Technical Operations, business unit stakeholders, Security, CIO Analytics, and business unit technical teams to assess opportunities, define use cases and success criteria, and design secure, reusable enterprise solutions. It leads hands-on evaluations and prototypes and guides solutions through integration and production readiness, with attention to operational support, reliability, privacy, cost, AI quality, and human oversight.

Requirements

• Bachelor's degree in computer science, information technology, engineering, or equivalent professional experience.
• 7+ years in software, platform, integration, or solutions architecture roles, with hands-on production engineering, technical leadership, and service-provider or customer-facing experience.
• Applied AI solution design experience, including LLM workflows, retrieval when appropriate, tool/agent integration, quality evaluation, model-selection tradeoffs, and non-AI alternatives.
• Enterprise service integration experience with cloud architecture, REST APIs, MCP, identity and authorization, operations tooling, and reusable platform and service patterns.
• Knowledge of security and service reliability, including data protection, threat modeling, auditability, observability, resiliency, human oversight, and production readiness.
• Engineering and advisory skills, including Python or TypeScript prototyping, architecture decision records, delivery tradeoffs, collaboration with service owners, and cross-team facilitation.

Nice To Haves

• Experience with AWS AI services, Claude, Kong Konnect AI/MCP integration, Client or CloudWatch, CI/CD, and engineering managed services in a regulated enterprise.

Responsibilities

• Partner with ES service owners, Technical Operations, and business unit stakeholders to understand service requirements, operational friction, and customer outcomes, and assess where AI is appropriate.
• Define use cases and success criteria; assess feasibility, value, cost, risk, and reuse before recommending experiments or enhancements to existing and new ES services.
• Architect AI-enabled capabilities within ES cloud, identity, API/MCP, integration, connectivity, and observability services using secure, reusable enterprise patterns.
• Lead hands-on evaluations and prototypes, and guide solution development and integration through production readiness with clear engineering acceptance criteria.
• Design secure, supportable operations with service engineering and Technical Operations, including evaluation, telemetry, access controls, runbooks, incident response, and rollback.
• Present evidence-based options to ES and business unit leaders, explaining service value, reliability, AI quality, cost, privacy, and human-oversight tradeoffs.
• Lead cross-functional architecture reviews and mentor engineers.
• Coordinate solution delivery with business unit technical teams, Security, and CIO Analytics on dependent applications and integrations.
• Translate architecture into demonstrable outcomes, communicate delivery risks, and maintain clear service and platform accountability.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior