Top Artificial Intelligence Software Engineer Jobs

The Frontend Engineer will lead frontend development efforts, unify product interfaces, enhance tooling, maintain UI standards, and contribute to full-stack projects.

The Data Engineer will design and implement scalable data pipelines, build data infrastructure, ensure data quality, and collaborate with teams for analytics and compliance.

As a Senior Support Engineer, you will enhance customer support for LanceDB by building infrastructure, maintaining knowledge-bases, troubleshooting customer issues, and collaborating with engineering teams. Your expertise in distributed databases and proficiency in Rust and Python will help optimize cloud-native database deployments.

Design, build, and operate backend services and APIs for affiliate systems (tracking, attribution, commission settlement, partner management, anti-fraud). Own end-to-end service lifecycle, ensure production reliability, scalability, and correctness for financially sensitive workflows.

As a Senior Software Engineer, you'll lead frontend development using React and WebGL, optimize performance, and mentor teammates in a collaborative design environment.

As a Software Engineer, contribute to advanced applied AI systems, build backend services and collaborate with ML engineers, ensuring reliability and performance.

As an AI Product Engineer, you will develop and deploy AI-driven software solutions, collaborate with customers, and optimize applications for real-world impacts.

The Mobile Engineer will develop and enhance the Amelia mobile application, focusing on high performance and scalability across platforms. Responsibilities include mobile app design, integration with third-party libraries, and collaboration with stakeholders for product improvements.

As a Full Stack Engineer, you'll develop AI-powered manufacturing applications, integrating real-time AI models and handling large-scale data pipelines while creating user interfaces for decision-making.

The role involves designing and implementing a distributed data processing engine, optimizing performance, and collaborating with product teams to enhance agricultural insights.