Principal AI Engineer

UTA seeks a Principal AI Engineer to lead the design, development, and delivery of intelligent software systems that bring together enterprise application architecture, full-stack engineering, data science, and machine learning. In this highly visible, hands‑on leadership role, you will build and scale production‑grade platforms and AI‑enabled products that power critical workflows, decision‑making, automation, and business insight across the organization.

The ideal candidate combines deep software engineering expertise with strong applied AI and data science capability, and has a proven ability to mentor engineers, shape technical direction, and partner cross‑functionally to turn complex business problems into scalable, secure, and reliable solutions.

• Lead the design, development, and deployment of machine learning, statistical, and AI‑driven solutions that support automation, prediction, decision‑making, and personalization.

• Own end‑to‑end delivery of AI‑enabled products and services, from problem framing and data exploration through model development, application integration, deployment, and monitoring.

• Evaluate and implement appropriate approaches across machine learning, analytics, and natural language processing based on business needs and technical constraints.

• Partner with data and platform teams to build robust pipelines, reusable services, and scalable environments that support production AI workloads.

• Design and develop scalable, secure, cloud‑native applications and backend services that integrate AI, data, and business workflows into enterprise platforms.

• Lead end‑to‑end full‑stack engineering across backend services and modern web applications, including APIs, data models, service integrations, and internal tools.

• Architect systems using modern cloud patterns such as microservices, event‑driven design, and managed services, ensuring reliability, observability, and scalability.

• Provide architectural leadership across integrations with enterprise systems and third‑party platforms.

• Productionize AI and machine learning solutions using modern ML Ops and software engineering practices.

• Establish standards for testing, deployment, observability, drift detection, retraining, and documentation.

• Drive quality, automation, and performance in systems where accuracy, resilience, and reliability are critical.

• Serve as a hands‑on technical leader and player‑coach, mentoring engineers while actively contributing to design and implementation.

• Help define technical strategy and roadmap priorities for AI, data, and application development.

• Lead execution of complex, cross‑functional initiatives and act as a senior escalation point for technical decisions and trade‑offs.

• Foster a culture of engineering excellence, accountability, and continuous improvement.

• Partner with Product, Engineering, Data, and business stakeholders to identify high‑value opportunities where AI and software can materially improve outcomes.

• Translate ambiguous business needs into clear technical solutions, communicating trade‑offs and risks effectively.

• Present complex technical work in a clear, actionable way to both technical and non‑technical audiences, including leadership.

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent experience; advanced degree is a plus.

• 10+ years of experience in software engineering, applied machine learning, data science, or related fields, including building and delivering production systems end‑to‑end.

• Strong hands‑on expertise in modern software engineering, including backend development, APIs, and scalable system design.

• Experience with full‑stack development, including modern frontend frameworks and service‑based architectures.

• Proficiency in Python and SQL, with experience in data manipulation, model development, and analytical workflows.

• Hands‑on experience with machine learning frameworks such as…