Top Artificial Intelligence Software Engineer Jobs in Phoenix – Mesa – Scottsdale, AZ

The Senior Application Architect will lead technical direction, oversee product development, manage Agile teams, and ensure solutions align with user needs and mission outcomes. Responsibilities include mentoring developers, managing risks, and collaborating on product roadmaps while leveraging architectural expertise in federal healthcare projects.

Design, build, and operate reliable backend systems while mentoring engineers, participating in design discussions, and improving system performance.

Seeking a skilled Front-End React Developer with 3-5 years of experience to develop responsive web applications, optimize performance, and collaborate in an agile environment.

The Software Engineer will build features across the stack, design AI/LLM-driven workflows, translate requirements, and collaborate closely with the founding team and customers.

As a Senior Backend Engineer at Edia, you will architect backend systems, supervise AI coding processes, and enhance AI-driven business automation.

The Principal Software Engineer will lead the technical architecture of a healthcare software platform, ensuring compliance and quality while mentoring a team. Responsibilities include overseeing software stack integrity from embedded devices to cloud infrastructure and collaborating across functions to meet regulatory and product goals.

The Technical Lead will oversee development efforts, mentor a team, make technical decisions, architect systems, and communicate with stakeholders to deliver high-performance solutions.

As a Senior Backend Engineer, you will architect and build core systems for subscription brands, focusing on API development and system reliability, while collaborating with the Product and Design teams.

As a Senior Software Engineer in Infrastructure, you'll manage GPU and cloud infrastructure, ensuring stability and enhancing developer experience in a fast-paced environment.

As a Staff Machine Learning Engineer, you will develop, productionize, and deploy ML models for clinical use, ensuring real-world effectiveness through hands-on coding and infrastructure building.