
An Embedded Build Team places a senior Beyond Data engineer full-time inside your business for a fixed 8 to 20 week engagement. They scope, design, build, and ship a production-grade AI system end-to-end, with tests, monitoring, and runbooks from the first commit. Faster than hiring, lower commitment, and backed by the full consulting team when they need it.
You have a funded AI project, a clear use case, and no engineers to deliver it. The board has signed off. The business sponsor is waiting. You have been quoted 6 to 9 months to stand up a team, and that is before the first line of code gets written.
Hiring is the obvious path, and it is also the slowest. Write the JD. Post it. Interview people who have titles but no shipping history. Make an offer. Wait out a three-month notice period. Onboard. Pick a tech stack. Then start.
By then, the moment has passed. The sponsor has cooled. Another priority has taken the oxygen. The project that had a clean runway 9 months ago is now a line item being questioned in the budget review. You did not fail to build the team. You ran out of time trying.
Scope call on Monday. We align on use case, success criteria, systems in scope, and the definition of done.
Engagement starts the following Monday. Laptop issued, access provisioned, first day on-site.
Weeks 1 to 2: embed in the business, pressure-test the scope, agree the architecture.
Weeks 3 to 6: build the first slice, demo weekly to real users, iterate on what they actually do.
Weeks 7 to 12: harden for production, integrate with the systems of record, load-test against real volumes.
Final 2 weeks: handover, documentation, runbooks, and the optional support path locked in.
Engagement ends with a production system, not a prototype. Nothing to productionise later.
A senior AI engineer embedded inside your organisation for a fixed engagement. They scope, build, and ship production-grade AI.
Learn moreProduction-ready AI agents, chatbots, and multi-agent systems, built senior-led end-to-end.
Learn moreThe operating layer your AI, automation, and analytics run on. Deployed in two weeks.
Learn moreA full-time embedded engineer moves faster than any part-time model or hiring process. Scope call Monday, engineer next Monday, first demo week 4, production by week 10 on a typical engagement.
Tests, observability, monitoring, and deployment pipelines from the first commit. Not bolted on after go-live. The system that ships is the system you can run.
A senior engineer embedded in 1 to 2 weeks, versus 6 to 9 months recruiting for a role that may not survive probation. Fixed duration, fixed scope, no long-term headcount commitment.
Final two weeks are spent writing runbooks, shadowing your ops team, and locking in an optional support path. When the engagement ends, somebody in your business or ours can run the thing.
| Phase | Weeks | What the engineer is doing | What you see |
|---|---|---|---|
| Embed | 1 to 2 | Scoping interviews with the sponsor and end users. Architecture design. CI/CD pipeline, test harness, and observability scaffolding stood up on day one. | A written scope doc, an architecture diagram, and a running pipeline with a hello-world deploy. |
| Build | 3 to 6 | First functional slice of the system. Weekly demos to real users. Tests written alongside the code, not after. | A working system used by real people by week 4. Weekly demo recordings. |
| Harden | 7 to 12 | Iteration on user feedback. Integration with systems of record. Load testing, error handling, cost controls, and security review. | A production-ready system passing your change advisory board and security sign-off. |
| Handover | Final 2 | Runbook writing. Documentation. Shadowing your ops or internal engineers. Locking in the optional support path. | Runbooks your on-call person can follow, documentation your next engineer can read, and a clear support arrangement. |
Engineering discipline is concrete from the first commit: version-controlled infrastructure, automated tests running on every push, structured logs, metrics, alerting, and deployment pipelines that roll back on failure. You get the standard of a senior in-house team, without building one.

A senior Beyond Data engineer joins your standups, gets issued a laptop or a VPN token, sits with your business sponsor in week one, and starts scoping. By week four they are demoing a working slice to the people who will use it. By week ten the system is in production, running on your infrastructure, with a monitoring dashboard your ops team can actually read and a runbook your on-call person can actually follow.
This is not an offshore contractor. It is not a staff aug body-shop. It is one named senior engineer with the full Beyond Data toolkit, the engineering standards we apply across every client, and the rest of the consulting team on the other end of a Slack channel when a harder problem lands.
An automated intelligence layer deployed into your business in two weeks. Your AI agents, dashboards, and automation run on it from day one.
2 weeks
to AIS live with first source systems
A funded AI plan in 6 to 10 weeks, not 6 to 10 months, for leaders who want direction before delivery.
6-10 weeks
board question answered with a funded plan
30-minute call, no slides, no obligation. We'll tell you plainly whether this is the right fit for what you're trying to do.
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