AI and automation
Forward deployed AI engineers who ship agents inside your business.
A forward deployed AI engineer joins your team remotely: your chat, repositories, standups and tools. They work on your real data and systems, build agentic workflows with your people, and take them to production with permissions, evaluation and handover. For a defined project instead, see AI automation.
When does a forward deployed engineer fit?
Choose this when the hard part is your context, not the model.
- You have several AI use cases and need someone inside the team to find the one worth shipping first.
- Your data and systems are internal, messy or regulated, and an outside demo will not survive contact with them.
- Your team wants to learn to build and operate agents, not just receive one.
- A pilot works in a notebook and now has to reach production with real permissions and monitoring.
What you get
A senior engineer in your team
An engineer with more than 10 years of professional experience, working daily in your tools and repositories, during hours that overlap with Europe or the US.
Agents in production
Agentic workflows connected to your systems, with scoped tool permissions and human approval for consequential actions.
Evaluation on your cases
A test set built from your real examples, run before each release and reviewed with you.
Knowledge your team keeps
Decision records, runbooks and pairing sessions, so your engineers can operate and extend what we build.
How an engagement runs
- 01
Embed
Join your channels and repositories, meet the people who own the workflow, and agree access.
- 02
Find the first use case
Rank candidates by value, data access and risk; pick one that can reach production.
- 03
Build with your team
Ship in small reviewed increments, evaluated on your data, with approvals where actions matter.
- 04
Hand over or scale
Document, train your team, and either hand over or add capacity for the next workflow.
Architecture, permissions, evaluation, ownership
Agent architecture
Tool-calling agents and multi-step workflows designed around your systems, with the model kept replaceable.
Permissions
Each tool has a written scope. Production credentials and write actions stay under your control.
Evaluation
Fixed test sets check correctness, source support, unauthorized actions and cost per task.
Ownership
You own the code, prompts, evaluation data and infrastructure accounts.
FAQ
What is a forward deployed AI engineer?
An engineer who works inside your team instead of at arm's length. They learn your workflows and data first-hand and build AI agents that fit them, instead of handing over a generic solution.
Is the engineer on site?
No. We work remotely, embedded in your tools and communication channels, with working hours that overlap with Europe and the US.
How is this different from a dedicated team?
A dedicated team adds engineering capacity to your roadmap. A forward deployed AI engineer focuses on finding, building and operating AI agents in your business.
How is it priced?
As monthly capacity, quoted after a short discovery call. Scope, length and access are agreed before work starts.
Which models and frameworks do you use?
We choose per use case from evaluation results, data requirements and cost, and keep the model replaceable.
Next step
Tell us where AI should help first.
Describe the team, systems and workflows involved. We reply with a proposed engagement and a first use case.