Job Summary
The IT Architect 3 - AI Software Engineering & Architecture is a hands-on principal-level architecture role focused on enterprise platform services, scalable APIs, cloud-native architecture, AI-assisted software engineering, and Digital Twin integration. The role will lead the evaluation, adoption, and enterprise implementation of AI-powered software engineering platforms and modern cloud-native architecture initiatives. The ideal candidate combines strong software architecture expertise with hands-on backend development, Kubernetes, DevOps, enterprise architecture, and AI-assisted engineering experience. Strong experience with NVIDIA technologies and a good understanding of Digital Twin concepts are required.

Key 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, Security, DevOps, and Platform Engineering teams to deliver scalable and secure solutions.
• Review emerging technologies across autonomy, embedded systems, remote services, Digital Twin, simulation, 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.
• Drive enterprise adoption of AI-powered software engineering and modernize software development through AI-native engineering practices.
• Build scalable cloud-native architecture solutions and define engineering governance standards.
• Improve developer productivity through the effective adoption of AI-assisted development tools.

Required Qualifications
• 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 or 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.
• Experience with enterprise security standards and secure software development practices.
• Strong business acumen with the ability to align technical decisions with business objectives.
• Experience working within Agile/Scrum environments.
• Hands-on experience with AI-assisted software engineering tools such as GitHub Copilot, Cursor, Claude Code, Devin.ai, or similar platforms.
• Strong experience with NVIDIA technologies.
• Good understanding of Digital Twin concepts and NVIDIA Omniverse.
• Strong technical leadership, communication, collaboration, and problem-solving skills.

Preferred Qualifications
• 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.
• Experience mentoring engineering teams and leading architecture reviews.
• Experience with cloud architecture strategy.
• Experience with Kubernetes architecture.
• Experience with AI governance.
• Experience with engineering productivity metrics.
• Experience with platform engineering.
• Experience with autonomy or embedded systems.
• Experience with remote services or related engineering platforms.

Certifications
• TOGAF Certification preferred.