Top Artificial Intelligence Software Engineer Jobs

Develop and maintain scalable web applications, design UI components, collaborate with cross-functional teams, perform code reviews, and stay current with web and AI-related technologies to ensure performance and scalability.

Build end-to-end user features under senior guidance: implement REST endpoints in Node.js/TypeScript, microservices in Python, maintain PostgreSQL schemas, process background jobs with QStash/Upstash, deploy to Cloudflare Workers/Pages/R2, write tests, and collaborate with product/design on React UI components.

Design and build intuitive, responsive, and performant user interfaces that bring AI capabilities to millions. Optimize cross-browser performance, implement streaming UIs, and scale frontend and backend systems including databases, caching, background jobs, and auth.

Build and optimize user-facing parts of the Starbridge platform using modern web technologies. Collaborate with product, design, and engineering to deliver high-performance, stable frontends, translate technical concepts for non-technical users, iterate quickly based on customer feedback, and maintain excellent UX/UI standards.

The Senior Software Engineer will design, build, and operate backend services, ensuring system reliability and performance while collaborating with others in a high-growth environment.

As a Senior Backend Engineer, you'll design and develop backend services using Golang and Python, focusing on scalability and integrating AI-driven features while collaborating with leadership.

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.

Build full-stack features for AI voice and chat products that scale to millions of conversations. Integrate ASR/TTS and conversational models, optimize production systems for latency and cost, participate in on-call rotations, and collaborate with product and ML teams to improve performance and user experience.

Build and maintain production-grade backend systems, ETL pipelines, data models, and integrations. Apply agentic AI workflows for data engineering and root-cause analysis. Provide technical leadership and mentorship, work directly with customers on integrations and deployments, lead POCs and pre-sales technical activities, and translate customer feedback into product improvements.

Lead end-to-end design, build, and operation of large-scale data pipelines on GCP/BigQuery, optimize data models and queries, integrate legacy SQL Server/SSRS systems, implement ETL/ELT and data quality frameworks, use intermediate Python for automation, and support BI/reporting with Power BI/Looker/Tableau while promoting AI tool adoption.