Top Artificial Intelligence Software Engineer Jobs

Lead a team of 4–6 engineers while spending 50–60% of your time building production systems. Own delivery, technical design, code quality, hiring, mentoring, and performance management. You’ll develop AI and agent products, integrate fragmented on-premise systems, improve scalability and caching, debug complex production issues, and collaborate directly with founders and customers. The role requires strong backend or full-stack engineering experience, cloud and distributed-systems expertise, and a willingness to work in person in San Francisco when based in the Bay Area.

Develop and sustain a cross-platform software test automation platform supporting mission requirements. Build Python and C++ applications, REST APIs, infrastructure automation, containerized workflows, and virtualized testing environments across Linux and Windows. Integrate DevOps, CI/CD, authentication, databases, and Infrastructure as Code tools. Troubleshoot systems, evaluate technical solutions, document implementations, and manage projects from requirements through deployment with minimal supervision.

Define and lead Omnissa’s GTM Engineering function, including its roadmap, architecture, tools, and team growth. Build production-grade signal, enrichment, routing, scoring, and agentic workflow systems across Sales, Marketing, Customer Success, and RevOps. Own Clay and its integrations with Salesforce and other GTM platforms, measure business impact, manage vendors, improve data quality, and drive adoption globally.

Design and implement DSP solutions for intelligence and defense applications. Research advanced DSP and machine learning algorithms for radar, electronic warfare, SIGINT, and RF geo-location. Develop signal-processing neural networks and transition them into real-time, field-ready software. Work end-to-end across signal collection, processing, software implementation, deployment, and operational integration in collaboration with multidisciplinary teams.

Own the reliability and success of payroll and HRIS integrations. Monitor and troubleshoot connection issues, validate enterprise customer integrations, diagnose API limitations, coordinate with customers and partners, and drive technical problems to resolution. Build scalable runbooks, monitoring practices, documentation, workflows, and automations that improve integration reliability, customer experience, and engineering efficiency.

Design, develop, and modernize backend services, APIs, integrations, and enterprise applications for a federal healthcare technology project. Lead technical implementations, conduct code reviews, mentor engineers, troubleshoot production issues, optimize performance and observability, and support secure Agile delivery. Collaborate with architects, QA, DevSecOps, and product teams while contributing to design reviews, release planning, documentation, and technical debt reduction.

Leads engineering strategy, architecture, delivery, and organizational development for Agiloft’s Contract Intelligence portfolio. Oversees Astra Agents, Contract Intelligence Graph, shared cloud-native platforms, APIs, IAM, AI assistants, and integrations. Partners with Product, Design, Applied AI, and Operations to deliver secure, scalable, reliable customer-facing systems. Manages distributed engineering teams, develops leaders, establishes operational metrics, guides responsible AI practices, and remains hands-on in architecture, code reviews, and technical decisions.

Develop and optimize enterprise ServiceNow platforms through scripting, configuration, integrations, automation, UI development, upgrades, and performance management. The role supports ITSM, ITOM, and ITAM modules; designs APIs and workflows; manages instances, cloning, archiving, and domain separation; conducts code reviews; partners with architects; and mentors junior developers.

Join a collaborative team as a Senior Software Engineer at Farsight, developing AI-driven applications for financial services, ensuring quality and enhancing product offerings.

Owns end-to-end product development across consumer and B2B experiences, including user-facing interfaces, microservices, APIs, instrumentation, and observability. Collaborates with design, product, go-to-market, and research teams to turn prototypes into polished products using machine learning technology. Responsibilities include code review, feature delivery, and maintaining high engineering quality.