Top Artificial Intelligence Software Engineer Jobs

As a Machine Learning Infrastructure Engineer, you'll design scalable infrastructure for AI research, manage deployments, and ensure reliable customer solutions, working directly with the CEO.

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

The role involves collaborating with customers to solve engineering challenges using machine learning, develop solutions, train teams, and improve products based on feedback.

Build and enhance a no-code platform by developing AI automation features, refining architecture, and collaborating closely with product and design teams.

The Senior Engineer (Growth) will build and optimize marketing sites and signup flows, run tests, automate CRM systems, and ship growth features, directly impacting revenue.

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.

Lead the development of Terra AI's backend system, collaborate with AI and ML engineers, and manage feature development and deployment. Build application pipelines and support team hiring.

As an AI Platform Backend Engineer, you'll design and deploy backend systems utilizing AI for real-world applications, optimize performance, and mentor junior engineers while working directly with clients to address complex challenges.

Build, scale, and harden the companywide experimentation and A/B testing infrastructure. Improve instrumentation, data governance, and metric trust while partnering with Product and Data Science. Drive technical decisions, mentor junior engineers, and own systems end-to-end to increase experiment throughput and reliability.

Design and build Machine Learning libraries, implement CI/CD pipelines, and support Ray-based compute environments, collaborating with ML experts.