Top Artificial Intelligence Software Engineer Jobs

Own technical pre-sales end-to-end: run demos on real data, scope and build integrations, lead multi-week POCs, write SOWs, hand off to deployment, and drive product feedback across Sales, Product, and Engineering.

Design and implement algorithms and software for orbit determination and maneuver execution, focusing on automated station-keeping and disposal.

Build and ship full-stack features and scalable data-processing pipelines for terabytes of audio; deploy and evaluate LLM/DSP solutions; iterate quickly with researchers and operations to collect and surface high-quality audio dataset insights.

Develop scalable data pipelines for autonomous driving, enhancing data extraction and labeling processes, and collaborating with cross-functional teams on ML models.

The Senior iOS Developer will create user-friendly mobile apps, manage application lifecycles, and collaborate with cross-functional teams to enhance product features.

The Staff Software Engineer will design scalable distributed systems for real-time data processing, lead technical initiatives, and mentor other engineers.

The role involves designing data ingestion and processing systems, writing scalable backend applications, and optimizing performance of business-critical endpoints.

Own end-to-end solution design and integrations for strategic enterprise accounts, connecting interface.ai's platform to core banking, telephony, and contact center systems. Serve as primary technical contact, deliver architecture blueprints and integration specs, lead production issue resolution, support pre-sales discovery, and produce reusable integration assets while feeding product and engineering with structured feedback.

Lead full-stack development of the Artificial Analysis website using a TypeScript/Next.js stack. Build UI and data visualizations, maintain PostgreSQL databases on Supabase, improve DevOps/CI/CD, mentor a small engineering team, and leverage LLMs and AI tools to accelerate development.

Own end-to-end deployments of Squint’s industrial intelligence platform: write production integrations, custom workflows and data pipelines, embed on factory floors and field sites, troubleshoot legacy systems and spotty connectivity, gather field feedback to shape product, and prove value to frontline users and executives.