Top Artificial Intelligence Software Engineer Jobs

Design, build, and own backend systems, services, APIs, data pipelines, and infrastructure. Solve distributed systems, scaling, concurrency, and performance challenges. Integrate and operate large generative AI models in production. Instrument and iterate in production, and design core platform infrastructure including third-party integrations, storage, security, and internal APIs.

Design, implement, and ship full-stack AI-powered applications on Unframe's platform; collaborate with product, customers, and research teams to extend platform and UI, integrate AI into production, and deliver clean, tested code.

Lead development of Hooks Android app from 0->1: design architecture, build native, performant media-rich features, integrate backend APIs, ensure UX quality, set Android best practices, and monitor performance and stability.

Own and run growth experiments across web and mobile: design, build and launch A/B tests, in-product growth mechanics (notifications, referrals, retention campaigns), optimize acquisition funnels and attribution, ship frontend and backend features end-to-end, and measure impact working closely with Product and Growth teams. Use analytics and AI-assisted development tools to accelerate delivery and improve engagement and retention.

Build and optimize high-scale, compute-heavy mobile recording systems for iOS and Android. Own performance, reliability, long-running capture workflows, custom Android hardware-adjacent systems, and production monitoring, testing, and debugging for field deployments.

Own and build the data platform: design real-time ingestion, schemas, and pipelines for high-volume ML jobs; consolidate and cleanse messy datasets; enable agent context and developer access to analytics.

You will manage revenue-generating systems at Maple, build pipelines, improve rep workflows, keep data clean, and prototype new tools.

Lead end-to-end development of a highly interactive, AI-driven-feeling single-page web app with a focus on exceptional UI/UX, performance optimization, and product ownership. Collaborate with customers, product, design, and engineering; ship features quickly; participate in code reviews, interviews, and culture-building.

Lead product growth by combining frontend engineering, product, and marketing. Analyze product usage with analytics dashboards, run top-of-funnel and engagement experiments, define metrics, and optimize revenue and pipeline pre- and post-sale.

Build and own backend platform systems around AI models: design APIs and database schemas in Python (FastAPI), create connectors, integrations, data pipelines, internal libraries/SDKs, and deployable infrastructure while collaborating with a small engineering and AI team.