Forward Deployed Engineer

About the role

The Forward Deployed Engineer (FDE) leads complex end-to-end deployments of SnapLogic's enterprise AI agent platform, Jean-Paul, into production alongside strategic customers. The role involves direct partnership with the customer's engineering and business teams, measuring success through production adoption, workflow impact, and field feedback.

This role is US-based, with San Francisco preferred. Travel to customer sites is up to 50%.

What You'll Do

• Teach, don't take over. Enable the customer's own users to build (skills, context, connections) so use cases continue to ship when you're not in the room.
• Expand across business functions. Each team you land in is a beachhead, not the destination. Identify adjacent functions with the next obvious win and seed champions there.
• Map a new landscape at every customer. Understand their tools, processes, and pain points. Conduct discovery like a business analyst, surface use cases worth doing, rank them by value, and make that value visible to their leadership.
• Own the technical landing. Deploy Jean-Paul into environments you've never seen, including customer VPCs, on-prem Docker hosts, and behind proxies and firewalls. Set up Single Sign-On (SSO), wire the AI provider, and get the first Managed Customer Platform (MCP) connection to a real customer system live.
• Win the connectivity war. Handle enterprise OAuth without dynamic client registration, redirect-URI allowlists needing an IT ticket, bot registrations, and mail routing. Build the context layer once the wire is live to make an agent trustworthy.
• Advise honestly. When Jean-Paul isn't the whole answer, propose the better or combined solution. Your credibility with the customer is the product.
• Be the escape hatch. Take on complex use cases directly, then turn what you built into patterns your team can repeat. Close the loop with product development by reporting issues and shaping the roadmap.

Requirements

• 5+ years of hands-on engineering or technical deployment experience, including real infrastructure work (Linux, Docker, networking, at least one major cloud, enterprise SSO/OAuth scar tissue).
• Built or deployed systems powered by Large Language Models (LLMs) or agents, and understand how model behavior affects user experiences.
• Know the difference between a connected system and a usable one, and have the judgment to build the context layer that makes an agent trustworthy.
• Comfortable sitting with a confused stakeholder, no spec, and can surface a future state they couldn't articulate themselves.
• Make other people better at something technical.
• Comfortable being first: there's no runbook here, you write it.

Qualifications

$150,000 - $200,000 a year

The above range is the approximate annual U.S. total compensation for this position. Final offer amounts are determined by multiple factors, including candidate location, experience and expertise, and may vary from the range listed.

All of our full-time employees receive a comprehensive benefits package.