Top Entry Level Artificial Intelligence Software Engineer Jobs

Build and maintain scalable full-stack applications across frontend and backend systems. Own features end-to-end, including user interface design and database optimization, while debugging production issues. Collaborate with founders on technical vision and roadmap, help establish engineering culture, engage with users, and contribute to the growth of an early-stage AI-powered insurance brokerage.

Develop and maintain AR/VR applications for supervising, manipulating, and controlling humanoid robots. Design spatial interaction workflows, integrate user interfaces with robotic perception and control systems, and deploy reliable applications on real robots. Prototype and evaluate interfaces through user studies, optimize distributed systems across headsets and robotic hardware, and collaborate with robotics, hardware, and software teams on testing, monitoring, and field support.

Engineering talent community for current and future PDW opportunities in Denver. Engineers may design, develop, integrate, test, and support production of tactical unmanned systems across mechanical, electrical, embedded software, and software engineering. Work may include mechanical design, PCB development, C/C++ embedded systems, Qt applications, QML interfaces, hardware integration, prototyping, troubleshooting, validation, and production support. Candidates should collaborate across disciplines, solve problems hands-on, and work effectively in a fast-moving environment.

Work directly with scientists to understand workflows, identify valuable use cases, drive customer pilots, configure and troubleshoot the AI platform, build lightweight solutions, train users, and convert customer feedback into reusable product capabilities. The role requires technical problem-solving, scientific fluency, strong customer engagement, teaching ability, independent execution, and comfort operating in an ambiguous startup environment.

Develop distributed computing algorithms, performance metrics, and analysis tools for Zoox’s Collision Avoidance System. Analyze petabytes of urban driving data, evaluate system performance, and collaborate with CAS Perception, Planning, Systems Design, Mission Assurance, and QA engineers to define autonomous-driving validation metrics and plans.

Build core multimodal backend systems for robotics and Physical AI, including real-time WebRTC video pipelines, hardware-accelerated codecs, petabyte-scale ingestion and storage, LiDAR and telemetry processing, sensor synchronization, and high-performance React and TypeScript interfaces. Engineers may work across infrastructure, spatial data, video, frontend, and AI-native product workflows while independently solving complex technical challenges.

Build and operate AI agent systems with customer engineering teams, helping move prototypes into reliable production systems. Design agents, improve evaluations, monitoring, scaling, and reliability, and train customers on the Mastra framework. Translate recurring customer challenges into open-source framework improvements, fix performance issues, ship new primitives, improve code quality, and influence the product roadmap through production insights.

Build customer-facing backend features using Django, optimize application performance, reduce technical debt, and collaborate closely with teammates. The role requires Python web development, computer science and algorithm fundamentals, strong research and debugging abilities, sound technical judgment, and ownership of work from development through delivery. This is an in-person position in Kitchener-Waterloo, New York, or San Francisco, with authorization to work in the US or Canada and ability to travel between both countries.

Lead development of high-performance Rust parsers, compilers, automata, indexes, and data structures for structured language-model generation. Optimize decoding-loop performance through profiling and benchmarking, integrate Python bindings and C++/CUDA components into inference engines, collaborate across teams, and maintain production-quality code through testing and CI/CD.

Design and build large-scale software systems that improve engineering development velocity, quality validation, cost, and performance. The role focuses on query optimization, query execution, compiler design, database internals, and distributed systems infrastructure. Responsibilities include operating production systems, solving complex computer science problems, collaborating across teams, mentoring junior engineers, and aligning delivery with current customer needs and future technology trends.