Forward-deployed engineers · Deploy
FDEs who take AI from pilot to production
Engineers who get your AI working inside your customers’ systems, not just in the demo, embedded with your team to take a pilot all the way to production.
What they do
Deployment, end to end
FDEs own the work between your product and your customer, the integrations, the data, and the real-world edge cases the demo never shows.
Scope with the customer
Sit with your customer to map the use case, the data, and what done looks like.
Integrate their systems
Wire your AI into the customer's CRM, data warehouse, and internal APIs.
Map the real workflow
Turn messy, real-world processes into something your AI can run reliably.
Handle the data
Connect data models, auth, and APIs across your product and their stack.
Take it to production
Own the path from a working pilot to a monitored production rollout.
Roll out and hand off
Runbooks, rollout checklists, and a clean handoff to both teams.
One execution system
Build, deploy, and validate
Plank is one embedded team across three modes, the one you’re on is highlighted. Pull in the others as a project needs them.
Forward-deployed AI engineering
FDEs who get the product live inside real customer environments.
Who it’s for
When the demo works but production doesn’t
For AI teams whose pilots keep stalling in the customer’s environment, the integrations, the messy data, the real-world edge cases, and whose core engineers are getting pulled off the roadmap to handle every deployment.
Trained for deployment
Formed through the Plank AI Accelerator
Every Plank FDE is developed through the Plank AI Accelerator, hands-on training in customer deployment, systems integration, and agent and workflow rollout, then embeds with pod-mates they have already shipped with.
Inside the Plank AI AcceleratorHow it works
From scoping call to production rollout
01
Scope
A short call to map the deployment, the customer's stack, and what done looks like. NDAs and IP assignment in place before any code.
02
Embed
Your FDE joins your repos, standups, and the customer's calls the same day, and reads the codebase and their systems.
03
Ship
Takes the pilot to a monitored production rollout, with runbooks and a clean handoff. Scale the pod up as deployments grow.
Common questions
What is a forward-deployed AI engineer?
An engineer who embeds with your team and your customer to take an AI product from a demo to something that runs in production, handling the integrations, the customer's data, and the real-world edge cases. Palantir made the role famous; OpenAI and Anthropic now build their enterprise businesses on it.
How is an FDE different from a product engineer?
A product engineer builds the product. An FDE gets it working inside a specific customer's systems, which is the part the build alone doesn't cover.
How is an FDE different from a solutions engineer?
A solutions engineer usually helps close the sale. An FDE writes the code, the integrations, and the rollout that take a pilot live.
When should you bring in an FDE?
When the hard part isn't building the AI, it's getting it live in your customers' messy systems, and that work is eating your core team's time.
Do Plank FDEs work in our codebase?
Yes, in your repos from day one, with NDAs and clean IP assignment in place before any code.
How do FDEs work with our engineering team?
They take the customer deployment work so your core engineers stay on the roadmap. Product changes go back to your team; they don't fork your code.
How fast can an engagement start?
Same day. After a short scoping call, your FDE reads the code, joins standups, and starts on the deployment.
Put an FDE on your hardest deployment
Tell us where your pilot is stuck. We’ll embed someone who can get it live.