Top Artificial Intelligence Software Engineer Jobs

Leads approximately 35 engineers across data engineering, integration engineering, and integration support. Owns delivery predictability, manager development, operational reliability, SLA performance, data platform modernization, integration scalability, and organizational clarity. Partners with product, data science, commercial, and delivery teams while overseeing healthcare integrations with EHR systems, enterprise data infrastructure, incident management, and client-facing reliability commitments.

Lead the technical direction of Samsara’s shared geospatial platform. Build scalable data ingestion and processing pipelines, map data models, spatial APIs, map-matching and routing foundations, and reusable platform capabilities. Scale storage, querying, and computation for real-time features, consolidate team-specific solutions, mentor engineers, lead cross-team technical projects, and represent the company in the geospatial community.

Lead and shape the engineering organization: own system architecture, set engineering standards, ensure code quality, design reliable infrastructure and deployments, build AI-assisted engineering workflows, mentor engineers, manage technical risk, and contribute to the product roadmap.

Lead Agile software teams developing secure full-stack web applications for defense and national security customers. Responsibilities include sprint planning, technical leadership, customer requirements gathering, frontend development with React, backend API development with Python, cloud deployment, containerization with Docker and Kubernetes, and collaboration on scalable, maintainable software systems using DevSecOps practices.

Own the technical customer lifecycle for startup clients, from deployment and activation through ongoing utilization. Identify high-impact AI use cases, integrate AI tooling into customer workflows, ship production software, and partner with engineering teams. Represent Scope Labs in the field, operate autonomously in ambiguous environments, communicate with technical and non-technical stakeholders, and relay customer insights to Product and Engineering to influence the roadmap.

Build and deploy full-stack custom solutions for strategic customers using monday.com APIs, SDKs, app frameworks, and automation tools. Lead customer discovery, translate business needs into technical designs, develop production applications, manage deployment and DevOps considerations, and support live solutions. Projects typically last 2–6 weeks and require strong communication, independent execution, and customer collaboration.

Build full-stack AI governance and observability features for Hex’s data platform. Responsibilities include developing React and TypeScript interfaces, backend language parsers, SQL generation, AI context systems, semantic models, agent audit tools, and workflows for governing and debugging AI-generated answers. The role requires solving front-end UX and backend scalability challenges while working with data teams and modern data warehouse technologies.

Build and lead development of full-stack agentic AI products for systems modernization. Responsibilities include creating coding harnesses and runtime layers, integrating source control, CI/CD, security, and developer tools, scaling coding-agent workflows, and partnering with customers, designers, and mission teams. The role requires production-grade, cybersecurity-compliant systems, strong product judgment, and close collaboration with forward-deployed engineering teams supporting national security missions.

Lead North America engineering teams for retirement products, provide technical and people leadership, drive architecture and delivery across multiple teams, adopt AI-native engineering practices, ensure operational excellence, and partner with product to shape roadmaps and execution.

Own important customer-facing product problems end to end, from understanding complex financial workflows to designing, building, and shipping reliable software. Collaborate closely with customers, product, design, and engineering while applying strong technical and product judgment. Drive adoption and customer outcomes after launch, create clarity from ambiguity, and raise engineering standards through hands-on product development.