Enterprise · Embedded AI engineering
Senior AI engineers, embedded in your team.
Engineers who've shipped production AI — in your stand-ups, your Slack, your PR review. Sprint, quarter, or full project. No "we'll come back with a deck" gaps, no juniors learning on your project.
Embedded engineering model
We sit inside the team, not next to it.
You've hired junior engineers and watched them learn on your project. You've hired consultants and gotten a deliverable that didn't survive contact with prod. Embedded AI Engineering is the middle path — senior engineers in your stand-ups, your PR review, your incident channel.
Every sprint starts with a written spec — what we'll ship, what success looks like, what's explicitly out of scope. Code lands through your normal PR process. Knowledge transfers by default. When we leave, your team owns it.
- Senior AI engineers who have shipped production systems
- Embedded in your stand-ups, Slack, and PR review
- Code lands through your normal CI + review process
- Spec-driven sprints — what we’ll ship, what success looks like
- Knowledge transfers by default; runbooks + handoff included
- NDA + IP assignment by default; clean exit when done
Sprint 02 · Agent reasoning loop refactor
aikoders-amanda wants to merge 7 commits into main from feat/reasoning-loop
All checks have passed
- ✓lint12s
- ✓unit tests · 248 passing1m 04s
- ✓eval suite · 96.4% accuracy2m 18s
- ✓deploy preview · vercel47s
How a sprint looks
Four-week embed, shipped to production.
- 01
Week 1 — Spec
Workshop the goal, map the systems, write the spec, agree on success criteria. No code yet — alignment is the cheap part of the project.
- 02
Week 2 — Build
Working end-to-end prototype on real data. PRs land through your review process. Daily stand-ups, Friday demo.
- 03
Week 3 — Harden
Guardrails, evals, observability, error handling. The 80% that turns a demo into something your team can defend in prod.
- 04
Week 4 — Ship + transfer
Production deploy, runbook, on-call doc, knowledge-transfer session. We leave; your team owns and can extend without us.
By the numbers
Engagement shape, not vendor games.
4 wk
Minimum engagement
Sprint pricing, fixed up front. Pause, extend, or end on any 4-week boundary.
Staff+
Engineer seniority
No juniors learning on your project. Production AI shipped before.
Yours
Code + IP
IP assignment by default. Your team can extend without us when we leave.
100%
Remote-friendly
Distributed by design. Written specs + PR review carry the work.
What you get
Real engineering work, not another slide deck.
In your stand-ups
Daily stand-up, sprint planning, retro. Same Slack channels, same Jira, same ownership.
Real PRs, real review
Code lands through your normal PR process. Your team reviews ours; we review theirs.
Architecture pairing
"Which model, which infra, which contract" decisions made at the whiteboard, not by email.
Spec-driven
Every sprint starts with a written spec. What we’ll ship, what’s out of scope.
Full-stack reach
Frontend, backend, infra, ML — wherever the bottleneck is, that’s where we work.
Right-sized engagement
4-week sprint, 3-month embed, or 6-month project. Pick what fits.
NDA + IP clean
Standard NDAs, IP assignment by default. Code your team writes with us belongs to your team.
Async-friendly
Remote-first by design. Written specs + PR review carry the work, not 8am stand-ups.
Outcomes, not hours
We commit to sprint outcomes, not hours-billed. Predictable budget, defensible deliverables.
Built for these teams
Where you need senior hands fast, without a full hire.
Scale-ups
Adding AI without slowing the existing roadmap
Existing team keeps shipping; we lift the AI work in parallel.
Series A / B
First AI hire would take 4 months — sprint NOW
Embed for the sprint that can’t wait; recruit the permanent hire on your own clock.
Enterprise IT
Internal AI initiatives, MVP → production
Cross-team initiative that needs senior engineering judgment, not a consultant.
Product Teams
AI feature on the roadmap, no in-house ML
Embed for the build, train the team during, leave a runbook on exit.
Platform Teams
Foundational AI infra (eval, prompt mgmt, RAG)
Senior platform engineers paired with your platform team for 1–2 quarters.
CTOs without an AI team
Strategic AI initiative without standing up a team
Architecture, pilot, and production deploy — without a six-month hiring cycle.
Common questions
What CTOs ask before they bring us in for a sprint.
How does pricing work — hourly or fixed?
Sprint pricing, fixed up front. A 4-week sprint is a fixed deliverable + cost, agreed at kickoff. Longer engagements (quarter, full project) bill in 4-week increments at the same rate so you can pause, extend, or end on any boundary. We don't bill by the hour and we don't surprise you with "scope creep" invoices — the spec is signed at week 1.What's the minimum engagement length?
4 weeks. Anything shorter and most of the time goes into ramp + handoff instead of shipping. The cleanest engagement shape is 4 weeks: week 1 spec, weeks 2–3 build, week 4 harden + ship + knowledge transfer.Who owns the code we write together?
You do. We work in your git org, code lands through your PR process, and IP assignment is in the master agreement. There's no AIKoders escrow, no licensing clause, no "you can keep using it but you can't show it to other engineers." When we leave, your team owns and can extend the codebase without us.How senior are the embedded engineers?
Staff-equivalent or above. Every engineer we embed has shipped production AI at scale — at least one prior 0→1 build, at least one prior LLM-in-prod deployment, and a track record of code review at companies whose engineering teams you'd recognize. We don't embed juniors; if your project benefits from junior labor, we'll tell you and point you at a different agency.Can you embed remotely or do you need to be on-site?
Remote-first by default. We're a distributed team, your team is probably distributed too, and the work happens in PRs + written specs + async demos — not in conference rooms. For specific sprint kickoffs or architecture workshops where being in a room helps, we'll fly out for a few days; otherwise it's Slack, GitHub, and Zoom for the working sessions.What happens at the end of the engagement?
Three deliverables: working code in your repo, a runbook + on-call doc, and a 1-hour knowledge transfer session for your team. After that, your team can extend without us. About a third of clients keep us on for a smaller ongoing engagement (eval-suite maintenance, monthly architecture review); two-thirds internalize.
Got a sprint that needs senior hands?
Embed senior AI engineers, ship in weeks.
Book a discovery call. We'll review your team, your project, and your deadline, then come back with a scoped embed plan and a roster.