Job description

About the Company Our client is a seed-stage AI company in San Francisco that deploys AI agents into the real operational workflows of Fortune 500 enterprises. The team is a high-bar mix of operators, engineers, and strategists, working AI-natively with no layers or process overhead. About the Role Forward Deployed Engineers are client-facing builders. They take an AI agent from the first client conversation to production, then move to a new enterprise and a new problem every few months. Customer-facing work and hands-on technical work are both heavy parts of the job: sitting in discovery calls, gathering requirements and mapping processes, then building POCs and shipping them. This is not a pure engineering, strategy, or research role; it sits between building a demo and running agents inside a Fortune 500 team. The role involves 20–40% travel to client sites. The team currently works 10am to 8pm, Monday to Friday, and is likely to move to Monday to Saturday. What You'll Do • Embed with client teams (finance, legal, ops, HR, IT) and map how work really runs, including exceptions and workarounds • Turn ambiguous business problems into agent workflows with success criteria, guardrails, and evals • Build prototypes and working agents, then drive adoption by training and sitting with end users • Present findings and results directly to C-suite stakeholders • Co-create KPIs with client leadership and measure the uplift after deployment Key Details • Location: San Francisco, CA (in-person, with 20–40% travel to client sites) • Schedule: 10am–8pm, Monday to Friday (likely moving to Monday to Saturday) • Employment: Full-time • Experience: 2+ years • Salary: $160,000 – $230,000 USD per year, plus equity • Visa Sponsorship: Available (H-1B) Benefits & Perks • Work with Fortune 500 companies on real operational workflows • Direct access to C-suite executives and operators • Own the full loop from problem discovery to production deployment • High-bar team of operators, engineers, and strategists • Value creation in days rather than quarters • Meaningful equity at an early stage • AI-native way of working • No layers or process overhead • Shape product, playbooks, and company scaling Interview Process • Screen • Vibe check • Technical screen • Case study • Sales interview • Onsite • Offer Required Candidate Questions Please include the following with your application: Basic Information • LinkedIn profile Experience • GitHub profile • Current company • Current title Logistics • Location • Do you need sponsorship now or in the future? • Are you open to relocating to the Bay Area?

Requirements

Must-haves

The role involves 20–40% travel to client sites. The team currently works 10am to 8pm, Monday to Friday, and is likely to move to Monday to Saturday.
Embed with client teams (finance, legal, ops, HR, IT) and map how work really runs, including exceptions and workarounds
Turn ambiguous business problems into agent workflows with success criteria, guardrails, and evals
Build prototypes and working agents, then drive adoption by training and sitting with end users
Present findings and results directly to C-suite stakeholders
Co-create KPIs with client leadership and measure the uplift after deployment
Location: San Francisco, CA (in-person, with 20–40% travel to client sites)
Schedule: 10am–8pm, Monday to Friday (likely moving to Monday to Saturday)
Employment: Full-time
Experience: 2+ years
Salary: $160,000 – $230,000 USD per year, plus equity
Visa Sponsorship: Available (H-1B)

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

Platform: manatal
Effort: medium