Top Artificial Intelligence Software Engineer Jobs

Build end-to-end full-stack features for cloud and factory-floor edge applications. Implement offline-capable, low-latency UIs and backend services, design APIs, write tests, troubleshoot production issues, and collaborate on shared libraries and developer tooling to support factory operators and supervisors.

Build production-grade automation workflows, integrations, custom nodes, and reusable patterns for strategic enterprise deployments. Embed with customers during focused on-site engagements, translate ambiguous business problems into practical technical solutions, and collaborate with Deployment Strategists, Product, and Engineering. Capture customer feedback for product improvements, create internal playbooks, and deliver scalable solutions that customers can operate independently. The role requires frequent travel, strong engineering and integration skills, customer-facing confidence, and sound technical judgment.

Build and maintain production-grade Golang backend services for an AI-driven investment platform. Design APIs and data pipelines supporting AI and reasoning systems, improve performance, reliability, and observability, review scalable architectures, and debug production issues. The role requires end-to-end system ownership, collaboration with AI and product teams, and mentoring as responsibilities grow.

Supports the CTO with technology research, AWS and AI exploration, backend development, cloud-native prototypes, REST API experiments, system design, technical documentation, and architecture planning. The intern will build proof-of-concept solutions using C#, Python, .NET, AWS services, and machine learning technologies while evaluating vendors and emerging tools.

Own the architecture and technical roadmap for core backend, infrastructure, and AI platform areas. Write and review production code, resolve complex production issues, improve reliability and scalability, and drive technical initiatives across teams. Build prototypes and customer-facing technical content, mentor engineers, establish engineering standards, and collaborate with cross-functional stakeholders in an in-person environment.

Build and maintain high-performance React Native applications for real-time 3D simulation and AI-driven training experiences on iOS and Android. Integrate streamed assets, progressive loading, live state updates, backend APIs, and mobile deployment pipelines. Develop reusable component systems, optimize performance, and translate product requirements into polished interfaces. Collaborate with product, machine learning, and graphics engineers to deliver production-ready mobile features.

Build scalable data pipelines, automation workflows, internal tools, and AI-powered quality-control systems. Lead data collection projects for frontier AI labs, establish quality frameworks, improve customer support processes, and manage cross-functional execution. Collaborate with technical and non-technical stakeholders to solve ambiguous operational challenges and deliver datasets and systems that improve advanced AI models.

Own and improve the company’s backend data and orchestration platform, including external integrations, event-driven pipelines, storage, monitoring, backend services, infrastructure, security, and access management. Build reliable systems with freshness and quality checks, simplify a rapidly grown data environment, document processes, communicate trade-offs, and guide junior engineers. The role requires hands-on production ownership in a remote, fast-paced company.

Lead and grow an engineering team while remaining a hands-on technical contributor. Own software design, implementation, debugging, testing, releases, evaluation infrastructure, reliability, customer outcomes, hiring, coaching, and team development. Partner closely with product, tax experts, customers, and engineering stakeholders to ship trustworthy AI-powered tax and accounting products. Establish evaluation practices, improve delivery execution, and connect technical decisions to adoption, trust, revenue, and operational impact.

Build end-to-end software products that transform ultraspectral sensing data, geospatial information, and AI outputs into customer-facing intelligence applications. Develop React interfaces, Python backend services, APIs, data integrations, and geospatial workflows. Deploy and operate reliable AWS services while maintaining testing, observability, performance, documentation, and production support. Collaborate with product, design, AI, infrastructure, and users to deliver capabilities from concept through deployment.