AI engineers who
get it to production — hire AI engineers
Bring in engineers who can take an AI idea from prototype to a reliable feature — connected to your data, tested on real examples and built into your product.
- Python + JSLanguages
- GPT · Claude · open sourceModels
AI specialists you can hire
Most AI work is careful engineering around a model. These roles cover both sides.
- 01
LLM application engineers
Build features on GPT, Claude or open-source models — prompts, retrieval over your documents, tool use and evaluation.
- 02
Chatbot & assistant developers
Support and internal assistants that answer from your help centre, policies or product data, with hand-off to a human.
- 03
AI agent developers
Agents that read emails, update your CRM or triage tickets, with approval steps wherever a person should decide.
- 04
Automation engineers
Connect email, spreadsheets, CRMs and internal tools so repetitive work runs on its own and is logged.
- 05
Data scientists & ML engineers
Data cleaning, analysis, classical machine-learning models and dashboards when an LLM is not the right tool.
- 06
AI-ready full-stack developers
Engineers who build the API, database and interface around the AI part, so it ships as a real product feature.
What our AI engineers work with
Everything we deliver under this service — pick one piece or combine several into a single project.
01Models & techniques
- OpenAI GPT
- Anthropic Claude
- Open-source models
- Retrieval-augmented generation (RAG)
- Prompt design and evaluation
- Tool use and function calling
02Engineering
- Python
- Node.js
- TypeScript
- PostgreSQL
- MongoDB
- AWS
- Docker
03Applied to
- AI chatbots and agents
- Document processing
- Workflow automation
- Analytics and reporting
- AI for small businesses
Getting an AI engineer started
- 01
Share the problem
Describe the task you want AI to help with, the data involved and your privacy constraints. We will tell you honestly if AI is a good fit.
- 02
Meet the engineer
Interview the shortlisted engineers and talk through how they would approach your use case before anyone starts.
- 03
Onboard into your tools
They join your Slack, Jira and GitHub, get access only to the data the task needs, and work in your repositories.
- 04
Weekly reporting
Weekly updates show what was built, how it performed on real examples, and what is planned next.
- 05
Prototype first
We recommend proving a narrow task on real data before hardening it for production. It keeps spend predictable.
- 06
Data handled carefully
Only the data a task needs goes to a model, business APIs are used by default, and an NDA is available on request.
Do you need an AI engineer or a software developer?
If your idea is “add a chatbot” or “summarise these documents”, much of the work is ordinary software engineering: getting data out of your systems, building an interface, handling permissions and logging. A strong full-stack developer with LLM experience often covers this well. A specialist AI engineer earns their place when quality depends on retrieval design, evaluation, prompt and model choice, or a custom machine-learning model.
Many teams start with one engineer who can do both, then add specialists once the first feature is live and the next problems are clearer. We can help you decide during a no-obligation consultation, and our team includes a data scientist and AI engineer alongside our developers.
Hiring AI engineers: common questions
Find answers to common questions about our services and how we can help your business.
Typical work includes chatbots and assistants that answer from your own content, AI agents that update your tools, document processing, workflow automation and AI features inside existing web or mobile apps. Where a classic machine-learning model fits better, they can build that too.
Put an AI engineer on your roadmap
Tell us the problem you want AI to solve. We will suggest the right profile and send a no-obligation quote.