CDAIO Enterprise Technology Architect (IT)

General Dynamics Mission Systems•Scottsdale, AZ

5d•Hybrid

About The Position

Leads enterprise architecture efforts across cloud, integration, AI, and security domains, producing decision-ready deliverables (executive summaries, risk registers, roadmaps, ConOps) that enable VP- and leadership-level decisions. Designs and governs AI platform architectures, including LLM access layers, API/MCP gateways, AI landing zones, and secure AI integration patterns compliant with NIST 800-171, CMMC L2, and GDMS IT policy. Develops and maintains architecture standards and templates across multiple domains (cloud, integration, security, data); contributes to and participates in Architecture Review Board (ARB) processes. Conducts enterprise integration architecture analysis, mapping system interfaces and interdependencies across Tier 1 applications to support investment decisions and AI readiness assessments. Produces AI-assisted architecture artifacts using approved AI tooling and skill libraries; actively contributes to the team's reusable prompt and skills repository to multiply output across the practice. Performs trade studies and technology evaluations — including POC design and execution — to recommend platform, tool, or solution selections with supporting business case, ROI analysis, and risk assessment. Supports Zero Trust architecture planning and implementation, with specific focus on data security, identity, and API-layer controls. Applies Model-Based Systems Engineering (MBSE) principles (SysML v2 or equivalent) to IT and enterprise architecture work. Identifies AI automation opportunities within architecture workflows and across IT operations; designs and advocates for automation solutions that reduce manual effort and increase consistency at scale. Engages cross-functionally with security, data, application, and engineering teams to align architecture decisions with CDAIO strategic objectives and organizational compliance posture.

Requirements

Bachelor's degree in Systems Engineering, or a related Science, Engineering or Mathematics field, plus a minimum of 10 years of relevant experience; or Master's degree, plus a minimum of 8 years of relevant experience.
U.S. citizenship is required.

Nice To Haves

Practical, hands-on proficiency with AI coding and architecture tools (e.g., Claude Code, Codex, or equivalent)
Knowledge of enterprise AI governance frameworks, including prompt security, least-privilege AI access design, AI risk registers, and responsible AI deployment practices.
Familiarity with cloud platform architecture across two or more major providers (AWS, Azure, GCP), including landing zone design, network connectivity patterns, and compliance-ready configurations.
Understanding of Zero Trust architecture principles and their application to data security, API security, and identity/access management.
Ability to produce executive-level architecture deliverables — system inventories, integration topology maps, AI readiness assessments, risk packages — that are audience-appropriate and action-driving.
Familiarity with enterprise compliance frameworks — NIST 800-171, CMMC L2, TOGAF
Creative thinker with demonstrated success leading the systems development life cycle
Collaborative team player eager to provide technical leadership and position others for success
Exceptional communication, presentation, and influence management skills, with notable record of securing buy-in on concepts and ideas
Experienced in the art of negotiation with ability to meet challenging customer requirements with win-win solutions
Commitment to ongoing professional development for yourself and others
Identifies opportunities to apply AI for continuous improvement and innovation

Responsibilities

Leads enterprise architecture efforts across cloud, integration, AI, and security domains, producing decision-ready deliverables (executive summaries, risk registers, roadmaps, ConOps) that enable VP- and leadership-level decisions.
Designs and governs AI platform architectures, including LLM access layers, API/MCP gateways, AI landing zones, and secure AI integration patterns compliant with NIST 800-171, CMMC L2, and GDMS IT policy.
Develops and maintains architecture standards and templates across multiple domains (cloud, integration, security, data); contributes to and participates in Architecture Review Board (ARB) processes.
Conducts enterprise integration architecture analysis, mapping system interfaces and interdependencies across Tier 1 applications to support investment decisions and AI readiness assessments.
Produces AI-assisted architecture artifacts using approved AI tooling and skill libraries; actively contributes to the team's reusable prompt and skills repository to multiply output across the practice.
Performs trade studies and technology evaluations — including POC design and execution — to recommend platform, tool, or solution selections with supporting business case, ROI analysis, and risk assessment.
Supports Zero Trust architecture planning and implementation, with specific focus on data security, identity, and API-layer controls.
Applies Model-Based Systems Engineering (MBSE) principles (SysML v2 or equivalent) to IT and enterprise architecture work.
Identifies AI automation opportunities within architecture workflows and across IT operations; designs and advocates for automation solutions that reduce manual effort and increase consistency at scale.
Engages cross-functionally with security, data, application, and engineering teams to align architecture decisions with CDAIO strategic objectives and organizational compliance posture.