IT Architect 3 (AI Software Engineering & Architecture)

The AES Group•Irving, TX

2d•Onsite

About The Position

We are seeking an experienced IT Architect to lead the evaluation, adoption, and enterprise implementation of AI-powered software engineering platforms and cloud-native architecture initiatives. This role will help define how software is developed across the organization by driving AI-assisted engineering practices, modern developer tooling, cloud architecture, and engineering productivity transformation. The ideal candidate combines strong software architecture expertise with hands-on backend development experience, cloud-native technologies, DevOps, Kubernetes, and AI-assisted software engineering tools such as Cursor, Claude Code, and GitHub Copilot. This individual will collaborate with engineering leaders, architects, cybersecurity, DevOps, and enterprise teams to establish AI engineering standards, governance frameworks, and next-generation software development practices. Good understanding of Digital Twin concepts and NVIDIA Omniverse is preferred.

Requirements

Hands-on Principal Architect role focused on enterprise platform services, scalable APIs, cloud-native architecture, and Digital Twin integration.
Must be a technical leader who takes ownership, works independently, drives architecture decisions, mentors engineers, and establishes engineering standards/playbooks.
Strong backend development experience with Java/Spring Boot or Python.
Strong expertise in Enterprise Architecture, Microservices, API Design, Distributed Systems, and Scalable Cloud Solutions.
Cloud: AWS preferred; Azure or GCP experience is also acceptable.
AI-assisted development is mandatory with hands-on experience using tools like GitHub Copilot, Cursor, Claude Code, or Devin.ai.
Looking for a modern, hands-on architect who actively builds solutions using AI—not someone focused only on documentation or presentations.
Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical discipline.
5+ years of experience in Software Architecture, IT Architecture, or Technical Leadership.
Strong hands-on backend software development experience using Java (Spring Boot) and Python.
Experience designing distributed systems, APIs, and cloud-native applications.
Strong understanding of cloud infrastructure, DevOps, server/storage technologies, and enterprise architecture.
Experience with Docker, Kubernetes, and containerized application platforms.
Knowledge of enterprise security standards and secure software development practices.
Strong business acumen with the ability to align technical decisions to business objectives.
Experience working within Agile/Scrum environments.
Excellent communication, collaboration, and problem-solving skills.

Nice To Haves

Experience with AI-assisted software engineering platforms including: Cursor, Claude Code, GitHub Copilot
Experience with agentic software development and specification-driven development.
Experience with AWS and/or Azure cloud platforms.
Knowledge of developer experience platforms and DevOps modernization.
Exposure to Robotics, Physical AI, Digital Twins, or Autonomous Systems.
TOGAF Certification preferred.
Experience mentoring engineering teams and leading architecture reviews.

Responsibilities

Lead the evaluation and adoption of AI-powered software engineering platforms including Cursor, Claude Code, GitHub Copilot, and emerging AI coding agents.
Define enterprise architecture standards for AI-assisted software development, engineering governance, and developer productivity.
Evaluate cloud capabilities and recommend architecture strategies supporting enterprise engineering initiatives.
Assess Kubernetes, Docker, containerization, and cloud-native technologies to determine optimal architecture solutions.
Design reference architectures and implementation patterns for AI-native software development.
Partner with engineering teams to implement agentic development workflows and specification-driven engineering practices.
Evaluate engineering productivity using data-driven metrics and establish continuous improvement strategies.
Work closely with Enterprise Architecture, GIS, Security, DevOps, and Platform Engineering teams to deliver scalable, secure solutions.
Review emerging technologies across autonomy, embedded systems, remote services, industrial systems, and related engineering domains.
Challenge existing architecture decisions and identify innovative technical alternatives.
Evaluate security, compliance, and governance considerations for AI coding platforms.
Mentor engineering teams on AI-assisted development, cloud-native architectures, and modern software engineering practices.
Collaborate with vendors and strategic partners to evaluate emerging technologies and industry trends.
Present architecture recommendations, pilot results, and technology roadmaps to engineering leadership.