Top Artificial Intelligence Jobs

Build and maintain full-stack software using TypeScript, Go, and Python, including backend, frontend, and architectural development. Collaborate with developers, designers, product managers, and Department of Defense stakeholders to develop AI-powered solutions, take products from concept to launch, conduct code reviews, and support customers through travel when needed.

Build and own production-grade APIs, services, and user-facing applications across Python and TypeScript. Architect event-driven systems, deploy serverless workloads, containerize services with Docker on AWS, and establish engineering practices and technical roadmaps. Partner with product and business stakeholders to deliver scalable features, manage projects from concept through deployment, and mentor future engineers. This first engineering hire will have substantial ownership in an early-stage startup and potential to grow into leadership.

Own a portfolio of strategic client accounts across onboarding, optimization, retention, renewal, and expansion. Monitor account health, lead QBRs, identify and close upsell opportunities, forecast renewals, mitigate churn, and coordinate with Sales, Implementation, Product, Marketing, and Engineering. The role requires presenting AI agent, marketing, and revenue performance data to technical and executive stakeholders while building account management processes in an evolving SaaS environment.

Guide new clients through software implementation, including kickoff meetings, project planning, platform configuration, data coordination, training, launch support, and early adoption. Manage timelines, milestones, documentation, and risks while coordinating clients and internal teams. Conduct post-launch health reviews, identify adoption barriers, create scalable onboarding resources, and improve implementation processes. Support client events, feedback collection, renewals, and expansion through successful implementation outcomes.

Leads the functional direction of complex enterprise CLM implementations from discovery and solution design through go-live, adoption, and optimization. Facilitates executive workshops, defines contracting processes, requirements, integrations, migrations, testing, and readiness standards. Advises customers on CLM best practices, AI governance, trade-offs, and change adoption while resolving escalations. Also improves delivery quality through disciplined scoping, reusable methodologies, quality oversight, and consultant mentorship.

Design and operate production-grade data pipelines, backend services, APIs, and agentic AI workflows. Build scalable systems that ingest, transform, and operationalize data for customer-facing and internal applications. Translate ambiguous operational workflows into reliable architectures, improve service observability and performance, and own technical decisions across data modeling, system design, security, and compliance.

Edit and produce shortform videos for YouTube Shorts and other platforms, collaborating with creators, researchers, and engineers to identify stories, develop concepts, capture footage, publish content, and iterate based on audience reception. The role owns the editing process and requires strong video-editing experience, creative vision, sound judgment, and alignment with the organization’s mission.

Drive sales growth and manage key client relationships by developing strategic business plans, leading contract negotiations, collaborating with internal teams, presenting quarterly business reviews, identifying new revenue opportunities, and ensuring client success while meeting sales targets.

Translate, edit, and culturally adapt English content into Spanish for digital platforms. Apply language standards, terminology, and reference materials; provide structured feedback to improve language models; collaborate with production teams on localization, content development, and quality assurance. This is an independent contractor role with flexible scheduling, fluctuating project availability, and a typical minimum commitment of 2 hours per day or 10 hours per week.

Conduct quantitative and machine learning research for real-time account-compromise detection. Design, train, evaluate, deploy, and scale production models while working with customer attack data. Build systems for streaming pipelines, feature stores, high-performance databases, and distributed infrastructure. Contribute production-grade code, establish technical standards, and advance detection capabilities in a high-autonomy cybersecurity startup environment.