The forward-deployed engineer who owns the feature end to end: interface, API, data and deployment, built inside your team and handed over documented.
Why this role exists
A design handoff is easy. Shipping a feature that works across the interface, the API, the data and the deployment is the hard part, and it needs an engineer who owns the whole path.
Most teams do not need more specialists. They need one senior engineer who takes a feature from ticket to production, works inside their codebase, and leaves the system running without us. That is exactly what this role is.
What this engineer owns
The engagement starts with a single senior engineer inside your team and grows only when the problem justifies it. These are the commitments behind the role; exact scope is agreed with your team.
Your full-stack engineer takes a feature from ticket to production: the interface, the API, the data model, the tests and the deployment. One person sees the whole path, so nothing is lost between handoffs.
What to verify: Ask who owns a feature from design to production, and who is called when it breaks at any layer.
They build front ends with real states: loading, empty, error and slow. Keyboard and screen-reader access, sensible validation and fast first render are part of the work, not a follow-up ticket.
What to verify: Ask how loading, empty and error states are handled, and how the interface is checked for accessibility.
APIs with clear contracts, data models that survive change, migrations that run safely, and permissions enforced on the server. The parts users never see are engineered as carefully as the parts they do.
What to verify: Ask how the data model is versioned, how migrations are applied, and where permissions are enforced.
Tests around the behaviour that matters, CI that blocks broken merges, and errors that surface with enough context to fix. The engineer leaves the codebase safer than they found it.
What to verify: Ask what the test suite covers, what CI blocks, and how production errors reach the team.
Deploys are small, frequent and reversible. Feature flags, staged rollouts and a rollback that works mean releasing is boring, which is the point.
What to verify: Ask how often the team ships, what a release looks like, and how long a rollback takes.
Every decision lives in your repository: code, tests, infrastructure definitions and written rationale. When the engagement ends, your team owns a system they understand and can change.
What to verify: Ask where documentation lives, and who on your side can make a change after handover.
How they work
The loop is simple and strict: specify the change, build it across the stack, prove it with tests, and ship it behind a switch with monitoring watching.
AI in the engagement
AI is not a separate offering bolted on. It is part of how this engineer works, and the judgment they bring is part of what your team absorbs.
AI tooling accelerates scaffolding, tests and boilerplate. What ships is code the engineer has read, understood and taken responsibility for.
AI assistants work best when the full picture is in view: the interface, the API, the data and the deployment. One engineer across the stack gets better results than fragments handed between specialists.
AI-assisted changes go through the same review, tests and evaluation gate as everything else. Nothing reaches users because it looked finished.
The engineer deletes code when a simpler design appears, and treats generated complexity with suspicion. A system your team can read is worth more than a clever one.
Working principles
Written scope, reviewed changes and visible trade-offs decide whether an embedded engineer actually works. We make those commitments explicit rather than implied.
The feature set, quality bar and deployment boundaries are written down before the first commit, and changes to them are agreed, not assumed.
Every change goes through review and CI like the rest of the codebase. The engineer is a team member, not an outside black box.
When speed, quality and scope conflict, the engineer shows the options and lets you decide, rather than picking quietly.
You work with the same engineer for the engagement, not a rotating bench. Continuity is what makes judgment about your domain compound.
Security & trust
This role touches your code, your data and your customers. Access, data boundaries and deployment permissions are agreed in writing before the first commit.
The engineer gets scoped access to the repositories, environments and data the work needs, nothing more, and access is reviewed and revoked at the end of the engagement.
Real customer data is read where it lives under your controls. Copies for development are minimised, masked and deleted when the work is done.
Keys and credentials live in your secret manager, never in code or chat, and are rotated when the engagement ends.
Commits, deployments and access are logged, so any change to your systems can be traced to a person and a reason after the fact.
Working arrangements
The engineer works remotely inside your rituals, in your cloud and your repositories, with builds and deployments running on infrastructure you control.
The engineer joins your stand-ups, reviews and planning from remote, and works in your repositories and issue trackers as a team member would.
Builds, deploys and infrastructure run in your accounts, with your keys and your logging. We do not route your systems through infrastructure you have not approved.
What the engineer may access, what may leave your environment and what must never leave are agreed in writing before development starts.
For discovery workshops, a critical launch or working through a legacy migration, on-site time is arranged deliberately.
How it starts
A paid two-week sprint proves the working relationship before anything longer is discussed. If it does not show real progress, you walk away.
Week one starts with the real product: what users struggle with, what the backlog actually says, and where the codebase resists change. The engineer sits with your team and reads the actual system.
One goal in writing: for example, one real feature shipped to production end to end, with tests, monitoring and a rollback path. Success criteria are agreed before building starts.
The engineer builds inside your codebase, opens small reviewed changes, and shows you working software, including what did not work, at the end of each week.
At the end of the sprint you see what shipped, the tests around it and what it changed for users, and decide together what comes next: extend, hand over or stop.
The ones your product runs on. The engineer works across the common web stacks and their clouds, and the point of the role is fitting into your codebase, not bringing a favourite framework.
Both. That is the point: one engineer owns a feature from the interface through the API and data to deployment, so the whole path is designed by one person.
Yes, and that is the default. They work inside your repositories, follow your conventions and improve the codebase they find, rather than starting something parallel.
Carefully. The engineer reads before rewriting, adds tests around behaviour before changing it, and replaces parts of the system when the evidence supports it, not for fashion.
No, but someone on your side owns the outcome. The engineer works with your product owner or domain experts, and hands the system over with documentation and tests.
The sprint is a fixed, paid engagement agreed before it starts, and its scope is written down. If it does not show real progress, you walk away with everything built so far in your repository.
Let's talk
Tell us about the product, the backlog and the constraints. We will help define a first sprint goal and the evidence needed to judge it.