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AI Engineers

Hire Dedicated AI Engineers Who Ship the Full Build

Add a vetted AI engineer to your team who can take a feature from raw data to a deployed, monitored system, without the time and risk of a direct hire.

50+ ERP and software projects. Zero failed projects since 2021.

End-to-End AI Build
📊
Data
🧠
Model
🚀
Deploy
📡
Monitor
1-2 wk
Typical shortlist time
100%
Screened on real builds
Flexible
Full time, part time or project
Free
Replacement if not a fit
Why It Matters

Most AI features fail between the demo and production

A working notebook is not a shipped feature. The gap is data pipelines, integration, deployment and monitoring, and that gap needs an engineer who has closed it before.

Beyond the Demo

Someone who can take a prototype to production

A promising prototype still needs clean data pipelines, error handling, and a deployment that holds up under real traffic. A dedicated AI engineer builds this properly instead of leaving it as a proof of concept.

  • Data pipelines that hold up in production.
  • The model that fits the task and budget.
  • Deployment and monitoring, not just a demo.
An engineer working on an AI system
Dedicated, Not Shared

One engineer who knows your stack end to end

Instead of splitting your AI backlog across a rotating team, you get an engineer who works only on your account, learns your data and systems, and moves faster with every sprint.

  • Direct access to the engineer, not a support desk.
  • Continuity across your whole AI roadmap.
  • Contracts that scale with your workload.
A remote engineer in a video call with a client team
What the Build Covers

The same four stages, every time

Whether the feature is a prediction, a generative tool or an automation, it moves through these stages.

Example: A Support Ticket Classifier
📊
Ticket data
🧠
Classifier
🚀
Live routing
📡
Accuracy checks
How Hiring Works

From requirements to a working engineer in about two weeks

1
Share requirements
Tell us the feature you want built, your data sources, and your existing stack.
2
Shortlist
We match engineers by the skills your build needs and send you 2 to 3 profiles within days.
3
Interview
You interview the shortlist directly and pick the engineer who fits your project and team.
4
Onboard
The engineer gets access to your data and systems and starts on your backlog in the first week.
5
Scale as needed
Add a specialist or a second engineer as your AI roadmap grows.
What's Included

Everything you need to run the engagement smoothly

🎯

Dedicated to your project

The engineer works only on your account, not split across other clients' work.

💬

Direct communication

You talk to the engineer directly on your tools, with no account manager relay in between.

📅

Flexible contracts

Full time, part time, or a fixed scope of work. Scale up or down with notice, not a long lock-in.

✅

Code quality checks

Code review and testing on every pipeline, integration and deployment before it ships.

🌐

Timezone overlap

Working hours arranged to overlap with your team for stand-ups and reviews.

🔐

Replacement guarantee

If the engineer is not the right fit, we replace them at no extra cost during the engagement.

What Changes

What a dedicated AI engineer changes for your roadmap

Faster
Features shipped to production
Fewer
Prototypes stuck in a notebook
Continuous
Knowledge of your systems
Monitored
Models once they go live
Model-agnostic
Choices based on your data
Lower
Cost than a full-time direct hire
Why Us

Why teams hire AI engineers through TCB Infotech

1
We ship AI features ourselves
We build AI into ERP and business systems, so our engineers are tested on real production work, not trivia.
2
Fast, honest shortlisting
You see 2 to 3 profiles, not a stack of resumes, and we tell you plainly if a fit is not right.
3
Direct access, no relay
You manage the engineer's day to day work directly, on your tools and your process.
4
Code you can keep
Every pipeline, integration and deployment is documented and handed over cleanly if the engagement ends.
5
No long lock-in
Scale the engagement up or down with notice, based on your actual AI roadmap.
6
Proven delivery
50+ ERP and software projects, with zero failed projects since 2021.
FAQ

Hiring AI engineers, answered

What does a dedicated AI engineer do?
They cover the full build of an AI feature: preparing the data, integrating the model that fits the task, wiring it into your application, deploying it, and monitoring it once it is live.
How is an AI engineer different from a machine learning engineer?
An AI engineer is a generalist who can work across data, model integration, generative features and deployment. A machine learning engineer focuses specifically on training and evaluating predictive models. If your need is a classic prediction or forecasting model, see our Machine Learning Engineers.
Can an AI engineer handle both traditional and generative AI work?
Yes. A generalist AI engineer can work on prediction, classification and generative features. For a project centered on one narrow area, such as retrieval pipelines or autonomous agents, a specialist may move faster; ask us and we will recommend the right fit.
What is the engagement model?
You can hire full time, part time, or for a fixed project. Contracts scale up or down as your AI roadmap changes, with no long lock-in period.
How do you vet AI engineers?
Every engineer is screened on data handling, model integration, deployment practices, and a practical build task before being shortlisted to a client.
What if the engineer is not the right fit?
We replace the engineer at no extra cost during the engagement, and hand over any work in progress to the new engineer with a short overlap.

Hire a Dedicated AI Engineer

Book a free consultation. Tell us what you need built, and we will shortlist AI engineers who fit your project and your team.

Book a Free Consultation →

No commitment. See a shortlist before you decide.

AI Engineer Hiring Features

How Hiring a Dedicated AI Engineer Works

From the requirements call to a monitored feature in production. Here is how we vet, match and onboard every AI engineer we place.

Core Process

Vetting, matching and onboarding, in that order

Vetting

Every engineer passes a practical build test

Before an engineer joins our bench, they are tested on data handling, model integration, deployment practices, and a hands-on task taking a small feature from raw data to a working endpoint. Only engineers who pass are shortlisted to clients.

  • Data pipeline and preparation fundamentals.
  • Model integration and evaluation.
  • A real build-and-deploy task.
A technical interview and coding assessment
Matching

You get a shortlist, not a resume pile

We match engineers to your specific requirements: the type of feature you are building, your data sources, and the timezone overlap that works for your team. You see 2 to 3 fitting profiles, not fifty.

  • Matched to the feature you are building.
  • Matched to your data sources and stack.
  • Matched to your working hours.
Reviewing a shortlist of engineer profiles
Onboarding and Management

A structured start, then you take the lead

The engineer gets access to your data and systems, reviews any existing work, and starts on your backlog in the first week. You manage priorities directly from there.

  • Access and environment setup in the first days.
  • A review of any existing prototypes or code.
  • Direct day-to-day management by your team.
An engineer onboarding onto a new project
What You Get

Everything included in the engagement

🎯

Dedicated engineer

Works only on your account, not shared across other clients' work.

💬

Direct communication

Access to the engineer on your own tools, with no account manager relay.

📅

Flexible contracts

Full time, part time, or a fixed scope, adjustable with notice as your roadmap changes.

✅

Code quality checks

Review and testing on every pipeline and deployment before it reaches production.

🌐

Timezone overlap

Working hours arranged to overlap with your team for stand-ups and reviews.

🔐

Replacement guarantee

A new engineer at no extra cost if the current one is not the right fit.