AI Architect

W2 - Client does not sponsor visa

Onsite in Irving, TX - must be local

Required Skills
Cursor, Claude Code, or GitHub Copilot (or similar AI coding tools)
Java/Spring Boot
Python
Distributed systems
APIs and integration services
Cloud-native platforms
Software architecture and engineering best practices
Prompt engineering
Agentic development workflows
Engineering metrics and productivity measurement
Infrastructure and cloud
Docker, containers, Kubernetes
IT security, server/storage
Security standards
DevOps

Technical Desired
Specification-driven development
Robotics, Physical AI, Simulation, or Digital Twin
AWS or Azure
Developer experience platforms

Soft Skills Required
Problem-solving and analytical thinking
Agile/Scrum team collaboration
Verbal and written communication
Cross-functional/distributed team collaboration
Ambiguity tolerance
Ownership and accountability
Technical documentation

Soft Skills Desired
Mentoring junior engineers
Technical leadership and design reviews
Stakeholder management and vendor collaboration
Continuous improvement
Global team experience

Disqualifiers (Red Flags)
No hands-on backend development
Limited API, integration, or distributed systems experience
Front-end only experience
No Agile/Scrum experience
Cannot contribute to cloud-native service development or troubleshooting

Key Responsibilities
Identify cloud capabilities and benchmark industry adaptation
Assess Kubernetes fit
Review ICS/ACT technologies (Remote Services, Minestar)
Challenge solutions and drive alternative architecture options
Partner with GIS, Security, and other teams on solution design
Evaluate and benchmark AI coding platforms
Define AI best practices, standards, governance, and adoption frameworks
Identify and execute AI pilot initiatives (Atlas, Physical AI, enterprise)
Design agentic, spec-driven, and autonomous development workflows
Measure developer productivity, quality, SDLC efficiency, and outcomes
Create reference architectures, implementation patterns, and guidance for AI-native development
Integrate AI into development lifecycle with architects, managers, product, and platform teams
Assess security, compliance, and governance for AI coding tools
Mentor teams on AI tools and modern engineering practices
Drive velocity, quality, technical debt reduction, and developer experience improvements
Collaborate with vendors, partners, and stakeholders on emerging capabilities and best practices
Contribute to engineering strategy, roadmap, technology selection, and long-term AI transformation
Individual contributor
Collaborate with: Engineering Directors, Managers, Principal Engineers, Architects, Technical Leads
Work across: Atlas, Physical AI, Autonomy Services, enterprise engineering
Partner with: Product Owners, Product Managers, business stakeholders
Partner with: DevOps, Platform Engineering, Cybersecurity, Enterprise Architecture
Engage with vendors and AI platform providers
Lead workshops, architecture discussions, PoCs, enablement activities
Mentor engineers and technical leads
Present recommendations, findings, pilot results, roadmaps to senior leadership

Required Education (Precise)
Bachelor's degree in Computer Science, Software Engineering, or related field (minimum)
o Master's + 3 years
o Bachelor's + 5+ years
o Associate's + 9 years
Internships not accepted as experience

Preferred Education
Master's degree in Computer Science or Software Engineering (preferred)

Preferred Certification
TOGAF certification (nice-to-have)