Service
Team
Extension
Senior engineers who join your team and work as if they were always there. Same tools, same standups, same standards — just more capacity and expertise exactly when you need it.
What you get
Senior engineers,
not capacity units.
Vetted before they arrive
Every candidate goes through a rigorous technical assessment and culture-fit interview. You meet them before they start — and you approve the match.
Embedded, not outsourced
They join your Slack, push to your repo, attend your retros. There's no "Edgeware process" layered on top of yours — they adapt to how you work.
Aligned incentives
Engineers are rewarded for long-term relationships, not placement volume. They care about the product you're building, not the hours on a timesheet.
Timezone overlap
We work with your hours. Whether you're in New York, San Francisco, or London — we schedule for real collaboration, not just async handoffs.
Rapid onboarding
Most engineers are productive in their first sprint. We handle the ramp-up scaffolding so you don't lose two weeks to setup and orientation.
Flexible scale
Start with one engineer, grow to a squad. Reduce back down when the sprint is done. No long-term headcount obligations or HR overhead.
Process
From brief to
first commit — fast.
Discovery call
We learn your stack, your team structure, and the skills gap you're trying to fill. Usually 30 minutes.
Candidate shortlist
Within 3–5 days we send you 2–3 matched profiles. You interview, you decide.
Contract & onboarding
Simple MSA, no lock-in. Your new engineer is set up in your tooling the same week.
Delivering in sprint 1
No six-week ramp. Most engineers are shipping meaningful work within the first sprint.
"We needed someone who could own the backend architecture — not someone we'd need to manage. Edgeware sent us exactly that person."
Most of our clients stop thinking of extended team members as external within the first month. The goal is always that the seam becomes invisible.
Forward deployed engineering
Forward deployed engineers,
for the last mile.
A forward deployed engineer (FDE) is a senior engineer who embeds inside your environment and owns an outcome end to end — framing the problem with the people who actually do the work, writing production code inside your systems, wiring it into your real data and legacy tooling, and staying until it is in daily use.
The role was popularized at Palantir and has since become standard practice at AI companies including OpenAI, Anthropic and AWS. The reason is simple: on an enterprise AI rollout the hard part is rarely the model. It is the messy data, the integration nobody documented, the workflow that exists only in someone's head, and the compliance rule that invalidates the happy path. That work cannot be specified in advance from the outside — someone has to be inside it.
We place forward deployed engineers on the same commercial terms as the rest of our team extension work: you interview and approve the match, you own the IP, and you scale the engagement with 30 days' notice.
Team extension, forward deployed, or a project team?
All three put senior engineers on your problem. They differ in who is accountable when the code reaches production and nobody uses it.
| Model | What you get | Measured by | Right when |
|---|---|---|---|
| Team extension | Senior capacity inside your team, which you direct | Work shipped against the plan you set | You know what to build and need more hands to build it |
| Forward deployed engineer | A senior owner embedded with your users and your data | Whether the system works in live use | Requirements are ambiguous, the work crosses departments, or adoption is the risk |
| Project team | A scoped build delivered as a package | Delivering the agreed specification | Scope is fixed, understood and stable up front |
When to ask for an FDE
- You have an AI feature that works in the demo and breaks on your production data.
- A platform you bought or built is live but nobody outside the pilot team uses it.
- The requirements only become clear once someone sits with the people doing the work.
- The project touches three teams and none of them owns it end to end.
- Your own engineers keep getting pulled off the roadmap to unblock one integration.
- You are shipping your product into an enterprise customer and the customer's environment is the obstacle.
What ours actually do
- Map your architecture, data and workflows in the first week, and say out loud what is really in the way.
- Write production code in your repo — integrations, pipelines, agent orchestration, the unglamorous glue.
- Sit in on the calls with the people who will use the thing, not just the ones who commissioned it.
- Set milestones at the outcome level and report blockers as product problems, not tickets.
- Leave documentation, tests and a handover your own team can carry — the engagement is meant to end.
Forward deployed engineering costs more per person than straight staff augmentation, and it concentrates knowledge in one or two people. When the risk is adoption rather than capacity, it is usually the cheaper mistake to avoid. If you are not sure which model fits, we will tell you honestly — often the answer is a standard team extension engineer and a clearer brief.
Talk to us about an FDELeadership
CTO-level direction,
without the full-time hire.
Some companies need senior technical leadership before they're ready for a full-time executive. Our Fractional CTO service puts experienced technology leadership in your corner — for as many hours as you actually need.
Talk to us about this ↓Technology strategy
Architecture decisions, stack choices, build-vs-buy trade-offs. Senior technical direction without the executive overhead.
AI-native leadership
Our CTOs work hands-on with modern AI models, APIs, and tooling. We help you build with AI where it genuinely adds value — not just where it's trendy.
Team & process
Engineering hiring, onboarding standards, code review culture. We help you build the team that outlasts the engagement.
Investor & board communication
Translating technical roadmap into business language. A credible technical voice in the room when it matters.
Expertise
Common stacks we extend.
Backend
Frontend
AI / ML
Infrastructure
Common questions