Top Artificial Intelligence Jobs

Own post-sales customer lifecycle for a TPRM SaaS product: onboard, drive adoption, enable integrations (SSO, Jira, Slack), support technical troubleshooting, partner on renewals/expansion, relay customer feedback to Product/Engineering, lead QBRs, and build playbooks as an early team member.

Lead market selection, design entry playbooks, and execute regional launches for an AI-native home health platform. Build KPIs, partner with Ops/Clinical/Product/AI, run field operations, codify reusable playbooks, and scale growth through de novo launches, acquisitions, and partnerships.

Own and build core data infrastructure for an AI-driven logistics platform: design and scale distributed backend systems, queues, databases, and real-time search; ensure reliability and performance; set backend technical direction; mentor hires and collaborate closely with founders in San Francisco.

Lead system architecture and integration for an ocean-deployed floating data center platform, define interfaces and requirements, run test and qualification campaigns, manage vendor procurement for major subsystems, and translate customer data center needs into platform-level specifications.

Lead a remote engineering org to define scalable SaaS architecture, build enterprise-ready platform foundations (reliability, observability, security), drive execution and delivery cadence, hire and develop engineering talent, and translate business priorities into technical plans while working with ML/AI and ad-tech use cases.

Outbound BDR responsible for prospecting and qualifying new business via cold calls, emails, and social outreach. Book meetings for AEs, maintain CRM data, collaborate with marketing, and consistently meet quota using sales tools and automation.

Work with the founding engineering team to build and ship a bounded project (eval infrastructure, ERP integrations, dashboards, or agent training pipeline). Partner with mentors, contribute to code reviews and design, learn production LLM/agent systems, and deploy customer-facing code. Must work in-person in the SF office for the internship.

Lead full-stack development of the Artificial Analysis website using a TypeScript/Next.js stack. Build UI and data visualizations, maintain PostgreSQL databases on Supabase, improve DevOps/CI/CD, mentor a small engineering team, and leverage LLMs and AI tools to accelerate development.

Collaborate with the founding team to design, prototype, and scale backend and infrastructure for an agentic AI assistant. Implement orchestration logic, API integrations, and LLM-driven workflows; build diagnostics, tests, and monitoring; improve agent reasoning and execution pipelines; participate in product and architecture discussions; document bugs and stabilize the platform for launch-readiness.

Own full-cycle enterprise revenue: self-source pipeline, qualify, design solutions with Sales Engineering, negotiate and close 100k+ ACV deals, and execute land-and-expand strategies. Lead VP/C-level conversations, align multi-stakeholder committees, maintain CRM hygiene and MEDDICC forecasting, and help build an enterprise sales playbook.