Forward deployed engineers who ship AI and software inside your team.
RefactorQ forward deployed engineers (FDEs) embed with your product, operations and engineering teams to turn high-value problems into production systems. Senior engineers, close to your users, accountable for the outcome.
When the hard part is getting AI into production, put engineers where the problem is.
Most AI initiatives stall between a promising demo and a dependable system. Forward deployed engineers close that gap. They learn your workflow first hand, build directly in your environment and stay until the system runs reliably, with your team able to own it.
Book a 30-minute FDE call
Tell us the workflow or product problem. A senior engineer will suggest the pod shape and a first milestone.
What a team of FDEs takes on.
Embedded AI and LLM application delivery inside your product and operations teams
Integration of AI agents and models with your data, APIs and core systems
Production hardening: evaluation, observability, security and cost controls
Hands-on enablement so your engineers own the system after we step back
How a forward deployed engagement runs.
Week one: sit with the business and engineering owners, map the workflow and agree the outcome to ship.
Build in your codebase, your cloud and your tooling, shipping to real users in short increments.
Harden for production with evaluation suites, monitoring, guardrails and runbooks.
Hand over through pairing and documentation, then scale the pod up or down as the roadmap needs.
Typical technologies our FDEs work with.
Questions about forward deployed engineers.
Clear, transparent answers about engagement model, deliverables, and production safety.
