Principal AI Software Engineering Lead

Job Title: Principal AI Software Engineering Lead

Location: Irving, TX, 75038 (Onsite)

Duration: 26 months contract

**Preferred locals to TX.

**Only those lawfully authorized to work in the designated country associated with the position will be considered.

Must Have Skills/Attributes: Cloud, DevOps, Java, Python.

Experience Desired: AI-Assisted Software Engineering & Developer Productivity (7 yrs); Backend/Platform Engineering (7 yrs); Backend/Platform Engineering (7 yrs); Software Architecture & Technical Leadership (7 yrs); Software Architecture & Technical Leadership (7 yrs)

Required Minimum Education: Bachelor’s Degree.

Preferred Education: Master’s Degree.

JOB DESCRIPTION:

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).

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.