Role: AI ArchitectLocation: Irving, TX
Work Model: Onsite
Duration: 26 Months
Must-Have SkillsPosition OverviewWe are seeking an experienced
AI Architect to lead the adoption of AI-driven software engineering practices and modern development workflows. The ideal candidate will have strong expertise in
Java, Python, cloud-native architectures, distributed systems, DevOps, and AI-assisted development tools. This role will drive AI strategy, establish engineering standards, evaluate AI platforms, and collaborate with cross-functional teams to modernize the software development lifecycle while improving developer productivity and software quality.
Required EducationOne of the following is required:
- Bachelor's degree in Computer Science, Software Engineering, or a related field with 5+ years of relevant experience
- Master's degree in Computer Science, Software Engineering, or a related field with 3+ years of relevant experience
- Associate's degree with 9+ years of relevant experience
Note: Internship experience will
not be considered toward the required experience.
Preferred Education- Master's degree in Computer Science or Software Engineering
Preferred Certification- TOGAF Certification (Nice to Have)
Required Technical Skills- AI coding platforms such as Cursor, Claude Code, GitHub Copilot, or similar tools
- Java and Spring Boot
- Python
- Distributed Systems
- REST APIs and Integration Services
- Cloud-Native Application Development
- Software Architecture and Engineering Best Practices
- Prompt Engineering
- Agentic AI Development Workflows
- Engineering Metrics and Productivity Measurement
- Cloud Infrastructure
- Docker, Containers, and Kubernetes
- IT Infrastructure (Servers & Storage)
- Security Standards and Best Practices
- DevOps Methodologies and CI/CD
Preferred Technical Skills- Specification-Driven Development
- Robotics, Physical AI, Simulation, or Digital Twin technologies
- AWS or Azure Cloud Platforms
- Developer Experience (DevEx) Platforms
Required Soft Skills- Strong analytical and problem-solving skills
- Excellent verbal and written communication
- Agile/Scrum development experience
- Cross-functional and distributed team collaboration
- Ability to work in ambiguous environments
- Ownership and accountability
- Technical documentation and architecture documentation
Preferred Soft Skills- Mentoring and coaching junior engineers
- Technical leadership and architecture reviews
- Stakeholder and vendor management
- Continuous process improvement
- Experience working with global engineering teams
Key Responsibilities- Evaluate cloud technologies and benchmark industry best practices.
- Assess Kubernetes adoption and cloud-native architecture strategies.
- Review existing ICS/ACT technologies, including Remote Services and Minestar.
- Challenge existing solutions and recommend alternative architectural approaches.
- Partner with GIS, Security, Platform Engineering, and Enterprise Architecture teams to design scalable solutions.
- Evaluate AI-assisted coding platforms and emerging AI technologies.
- Define AI engineering standards, governance, best practices, and enterprise adoption strategies.
- Identify, plan, and execute AI pilot initiatives across enterprise platforms, Atlas, and Physical AI programs.
- Design agentic, specification-driven, and autonomous software development workflows.
- Measure engineering productivity, software quality, SDLC efficiency, and developer experience.
- Develop reference architectures, implementation patterns, and AI-native engineering guidelines.
- Integrate AI capabilities throughout the software development lifecycle in collaboration with engineering, product, and platform teams.
- Evaluate AI solutions for security, compliance, governance, and enterprise readiness.
- Mentor engineering teams on AI tools, modern software engineering practices, and cloud-native development.
- Drive improvements in engineering velocity, software quality, technical debt reduction, and developer productivity.
- Collaborate with technology vendors and AI platform providers to evaluate emerging capabilities and best practices.
- Contribute to long-term engineering strategy, technology roadmaps, platform selection, and enterprise AI transformation initiatives.
- Function as an individual contributor while providing technical leadership across multiple engineering teams.
- Lead architecture reviews, technical workshops, proof-of-concepts (PoCs), and enablement sessions.
- Present architectural recommendations, pilot outcomes, and strategic roadmaps to senior leadership.
Key StakeholdersThe AI Architect will collaborate closely with:
- Engineering Directors, Managers, Principal Engineers, Architects, and Technical Leads
- Product Owners and Product Managers
- Business Stakeholders
- DevOps and Platform Engineering Teams
- Cybersecurity Teams
- Enterprise Architecture Teams
- AI Platform Vendors and Technology Partners
Disqualifiers (Red Flags)Candidates will
not be considered if they have:
- No hands-on backend development experience
- Limited experience with APIs, system integration, or distributed systems
- Front-end development experience only
- No Agile/Scrum experience
- No experience developing or troubleshooting cloud-native services
