---
title: "Dedicated Development Team From $3,000/mo — Gigabit"
url: https://gigabit.agency/services/embedded-ai-teams/
description: "A dedicated development team of senior AI engineers inside yours: assembled in 2 weeks, shipping by Day 5, $3,000–$7,500 per engineer a month. No lock-in."
lang: en
---

Home (https://gigabit.agency/) / Services (https://gigabit.agency/services/) / Embedded AI Teams

Dedicated development team · Embedded AI Teams

# A dedicated development team of senior AI engineers, _embedded._

When you need senior AI/ML engineering capacity now and don’t want to spend six months hiring, we embed a forward-deployed pod into your team — **same sprint board, same Slack, same code-review bar.** The model behind every Gigabit engagement, available on its own.

Start a trial: https://gigabit.agency/discovery-call/?offer=embedded
IT staff augmentation, compared: https://gigabit.agency/compare/embedded-vs-staff-augmentation/

The problem

## Staff aug usually means throwing work over a wall. _Not here._

The offshore body shop gives you a résumé, no oversight, and code you have to rewrite. The Cheap-Vendor Tax. An embedded Gigabit pod is the opposite: named senior engineers, AI-first, with our own technical oversight, who work inside your process and **ship from Sprint 1.**

Weighing the alternatives? See how a dedicated team compares with IT staff augmentation (https://gigabit.agency/compare/embedded-vs-staff-augmentation/), or how the same engineers work as an offshore software development (https://gigabit.agency/services/offshore-development/) team from our Dhaka hub.

Who's in the pod

## A small, senior team.

Sized to the work — not a roster you have to manage.

### AI / agent engineers

Built RAG pipelines, multi-agent systems, and the structured-output plumbing that survives production.

### ML / data engineers

Pipelines, retrieval, embeddings, and the data hygiene most AI projects skip until it breaks.

### MLOps engineers

Evals, observability, versioning, and the reliability layer that keeps agents healthy.

### A delivery lead

Owns scope, cadence, and the relationship — so you have one accountable point of contact.

How we embed

## Inside your team, not over a wall.

### On your sprint board.

Same Slack, same GitHub, same code-review bar. The pod works inside your environment, not over a wall.

### Async-first, with overlap.

Built around 2–3 hours of US-Eastern overlap, so handoffs are clean and momentum never stalls.

### Senior, not staffed-up.

You get engineers who've shipped production AI — not juniors who learned a tool last quarter.

Pricing & trial

## You see the work before you commit.

The cost advantage is real — senior engineering without Bay-Area overhead — but it's the floor, not the pitch. The pitch is named engineers who ship.

$3,000–$7,500 / engineer / mo

By role and seniority. **2–4 week trial, no lock-in, 30-day notice.** Assembled in two weeks, first PRs by Day 5, full sprint velocity by Week 4.

See full pricing: https://gigabit.agency/pricing/
Start a trial: https://gigabit.agency/discovery-call/?offer=embedded

Embed or hire

## What it cost one client, both ways.

A Series B HR-tech company that had two senior seats open for four months. Their numbers, from the case study.

Dimension

Gigabit

Hiring in-house

Cost

$3,000–$7,500 / engineer / mo

$195K–$220K a year, fully loaded, per senior hire

Time to capacity

About 2 weeks to assemble, first PRs by Day 5

A 4–6 month hiring cycle

Three engineers for a year

$207,600

$600,000

Commitment

2–4 week trial, no lock-in

Permanent headcount

One engagement, not a market average. Read the full case study. (https://gigabit.agency/proof/team-augmentation-hrtech/)

Have an app that was built with AI tools and needs to reach a real launch? See how a pod takes a prototype to production. (https://gigabit.agency/services/prototype-to-production/)

The anti-positioning

We are **not** a staffing agency filling seats with whoever’s on the bench. A pod is a small, senior, accountable team with a delivery lead — forward-deployed to ship, and to level up your engineers while it does.

Embedded teams FAQ

## Questions about embedded pods

#### What is an embedded AI team?

A small pod of senior AI engineers who work inside your team: your sprint board, your Slack, your repositories and your code-review bar. Gigabit supplies the engineers and the technical oversight; you direct the work.

#### Is it cheaper to embed AI engineers than to hire them?

For one HR-tech client it was: three embedded engineers cost $207,600 a year against $600,000 for the equivalent US hires, and were productive in 2 weeks instead of after a 4–6 month hiring cycle. Hiring still wins when the work is permanent and you can fill the seats.

#### What does an embedded AI engineer cost?

$3,000–$7,500 per engineer per month, depending on role and seniority, with a 2–4 week trial and no lock-in.

#### How fast can a pod start?

Two weeks to assemble, first pull requests by Day 5, full sprint velocity by Week 4.

#### How is this different from offshore staff augmentation?

Named senior engineers, AI-first, with Gigabit's technical oversight, working inside your process and code-review standards — not résumés thrown over a wall. There's a 2–4 week trial and no lock-in.

Go deeper

## From the field notes

Forward-deployed · 9 min

### What is a forward deployed engineer?
https://gigabit.agency/insights/what-is-a-forward-deployed-engineer/

Forward-deployed · 7 min

### When to hire vs embed AI engineers
https://gigabit.agency/insights/hire-vs-embed-ai-engineers/

Vendor Evaluation · 4 min

### In-house, freelancer, or agency: who should build your AI agent
https://gigabit.agency/insights/in-house-freelancer-or-agency-ai/

All insights →: https://gigabit.agency/insights/

The delivery model

## Put a forward-deployed pod on your roadmap.

Tell us what you're trying to ship. We'll assemble the right small, senior team — usually within two weeks.

Start a trial: https://gigabit.agency/discovery-call/?offer=embedded
Explore the ladder: https://gigabit.agency/services/

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