Join an early-stage applied AI team to lead end-to-end enterprise deployments of AI agent systems. This high-ownership role works across engineering, product, and business, helping customers turn complex workflows into practical platform solutions while shaping the growing deployment function.
Own enterprise customer deployments from discovery and solution design through implementation, scaling, and ongoing customer engagement.
Work directly with customer teams to understand their workflows and build tailored agentic solutions on the platform.
Develop custom AI workflows, data integrations, production APIs, and agent systems within platform constraints.
Share deployment insights with product and engineering teams to inform platform improvements and product priorities.
Collaborate with company leadership and the deployment team on strategy, staffing, and how to scale customer delivery.
Two to six years of experience in forward deployed engineering, enterprise AI implementation, or applied AI roles.
A degree in computer science, engineering, math, physics, or a related technical field, with strong technical fundamentals.
Hands-on experience building or deploying AI agent systems and workflows, beyond basic chatbot applications.
Proficiency in Python and/or TypeScript, with experience building production APIs or data pipelines.
Experience in financial services, such as private equity, investment banking, insurance, or tax and audit, or in semiconductors.
Strong systems thinking and the ability to learn business domains quickly and translate needs into technical solutions.
Experience with cloud infrastructure and enterprise integrations is helpful; willingness to travel up to 50% is required.
Salary: $160,000 to $220,000 annually. Visa sponsorship is available.
On-site in San Francisco, California. New York-based candidates are also noted as preferred. Travel of up to 50% may be required.
Job details are sourced from the employer's original posting.
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