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

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.

As a Software Engineer in Reliability, you'll architect and manage multi-cloud GPU infrastructure, ensuring performance, security, and scale while debugging complex hardware/software issues.

The Senior Fullstack Engineer will deliver software products, collaborate with product and business teams, lead technical practices, and ensure high-velocity iteration on a mobile advertising platform.

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.

Lead a cross-functional engineering team to design and deliver SMART on FHIR applications embedded in EMR workflows. Champion AI-driven, agent-assisted development, collaborate with data engineering on Python/dbt/SQL pipelines, implement engineering best practices, and manage hiring, mentorship, and stakeholder communication while ensuring quality, reliability, and interoperability.

Build and operate Vic.ai's integration platform that syncs ERP and financial systems with Vic. Develop backend services (TypeScript/Node.js), design typed third-party API integrations, ensure idempotent, replay-safe job processing, deploy and monitor services on AWS, contribute to AI-assisted onboarding and adjacent backend domains (Elixir, Python), and drive architectural decisions for scalable, reliable systems.

The Staff Machine Learning Engineer will develop and maintain MLOps tools, optimize model performance, and collaborate on ML system architecture with a focus on enhancing developer experience.

Seeking a full stack engineer to develop applications, requiring skills in Node.js, SQL, and modern JavaScript frameworks with a focus on scalability and performance.

Design, build, and scale low-latency distributed platform components; define technical vision and architecture; collaborate with product and ML teams; evaluate build-vs-buy decisions; prototype research breakthroughs and deliver robust, production-grade services.