Top Artificial Intelligence Software Engineer Jobs

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.

Own customer deployments and rollouts of an AI product specialist: deploy, debug, train users, build deployment infrastructure and evals, define rollout metrics, gather product feedback, and push fixes. Travel frequently to dealerships and customer sites and work from San Francisco when not traveling.

Build and ship user-facing features across the stack, collaborate from concept to production, contribute to system design, iterate from user feedback and data, and own product-quality and performance improvements.

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.

Own customer onboarding and implementations, integrate Stuut with ERPs (NetSuite, SAP, Salesforce), write production-quality code and automations, collaborate with Sales and Product, build documentation and internal tools, and travel to client sites to deploy solutions and gather product feedback.

Hands-on senior full-stack engineer focused on backend and data: build services, APIs, and Postgres schemas; own ETL and vendor SDK integrations; contribute to React frontend; author technical specs; improve CI/CD, Terraform, and dev tooling; ensure reliability, security, and compliance for PHI/PII and payments.

Develop and optimize mobile applications using OOP and C/C++ and/or Java with emphasis on audio DSP, streaming audio, and integration with audio middleware (FMOD, Wwise) and game engines. Work on audio technologies (OpenAL), mobile platforms (Android/iOS), and performance optimization. Bonus experience in HRTF, ambisonic arrays, audio metadata, and VR is desirable.

Act as the technical liaison to healthcare clients to deploy and operate Synapsis AI. Lead data mapping, SQL logic, ETL pipelines, integrations, and event-driven workflows. Coordinate release schedules, support cybersecurity reviews, monitor system health, automate operational tasks, capture client requirements, and translate them into engineering deliverables while partnering with clinical and product teams.

Lead architecture and delivery of scalable, high-performance backend systems; design and ship AI-native, agentic workflows; mentor engineers; collaborate with product and stakeholders; own complex multi-area project lifecycles; ensure reliability, security, and performance; document architectural decisions.

Design and build backend services, APIs, SDKs, and user-facing systems enabling secure agent-to-agent financial interactions. Implement cryptographic identity, payment workflows, transaction processing, reputation tools, and scalable infrastructure for AI-native financial products.