Top Tech Jobs & Startup Jobs

Build and improve a full-stack product that enables customers to manage AI agent workflows, including exception queues, reconciliation reviews, approvals, reporting, APIs, and agent SDK tools. The role involves frontend and backend development, real-time interfaces, workflow reliability, traceability, customer feedback, and polished user experiences. Engineers work in person with customers and a small founding team to shape product direction and solve ambiguous technical problems.

Own infrastructure for deploying and operating AI agent systems across customer environments. Responsibilities include workflow reliability, CI/CD, secrets and access controls, database performance, observability, integration resilience, incident response, and on-call operations. The role works closely with engineers to build practical shared infrastructure, investigate production failures, and improve systems across deployments. This is an in-person San Francisco position with occasional extra hours and weekend commitments.

Build and deploy AI agents within enterprise workflows by embedding with client teams, mapping processes, defining KPIs and evaluation plans, creating prototypes, and driving adoption. The role combines engineering, analysis, and executive-level communication. Responsibilities include training users, iterating on deployed agents, presenting findings to senior stakeholders, codifying successful approaches, and identifying additional AI transformation opportunities. The position is onsite in San Francisco with 20–40% client travel.

Build and maintain Varick OS and production agents: durable runtime for long-running workflows, provider-agnostic model routing, eval and trace infrastructure, and deployment tooling for single-tenant client environments. Ship LLM-backed systems, improve reliability, and generalize repeatable workflow patterns from forward-deployed audits.