Hire AI engineers

AI engineers who get features into production

Add engineers who combine software engineering with practical language-model experience, so AI features move from prototype to something your customers can rely on.

The problem

The AI skills gap

Many teams can build an AI demo. Fewer can make it accurate, safe, affordable and maintainable.

No evaluation

Nobody can measure whether a prompt change made things better or worse.

Rising model costs

Usage grows faster than the value delivered.

Safety and privacy concerns

Customer data and model outputs handled without clear controls.

Scarce talent

Engineers with production AI experience are hard to hire.

Our approach

Software engineers with AI depth

Engineers are assessed on both strong software engineering and practical experience shipping language-model features.

What you get

  • LLM application patterns: tools, structured outputs and retrieval
  • Evaluation sets and regression testing for AI behaviour
  • Cost, latency and model selection trade-offs
  • Guardrails, privacy and human-in-the-loop design
  • Production integration in Python or TypeScript

Capabilities

What our Hire AI Engineers work covers

Pick one capability or combine several. Each is scoped, estimated and delivered with the same engineering standards.

LLM feature development

Summaries, extraction, classification and assistants inside your product.

Retrieval systems (RAG)

Answers grounded in your documents, with sources.

AI agents

Agents that use tools and APIs with defined permissions.

Evaluation and monitoring

Test sets, quality metrics and production monitoring.

Automation engineering

n8n and custom workflows that put AI to work across your tools.

How we work

How we deliver Hire AI Engineers

  1. Brief

    Share the AI use case, data, stack and constraints.

  2. Interview

    Meet shortlisted AI engineers.

  3. Onboard

    The engineer joins your team, tools and review process.

  4. Scale

    Adjust capacity as AI work grows.

Technology

Technology we use

Chosen for reliability, maintainability and fit with your existing stack.

Models

  • OpenAI
  • Anthropic Claude
  • Open-weight models

Frameworks

  • LangChain
  • LlamaIndex
  • Model Context Protocol (MCP)

Data

  • pgvector
  • Vector databases
  • PostgreSQL

Languages

  • Python
  • TypeScript
  • Node.js

Use cases

Where teams put this to work

Common starting points. Your process will have its own details, which is why every engagement starts with discovery.

  1. 01

    AI features in a SaaS product

    Assistants, summaries and smart search for your users.

  2. 02

    Internal knowledge assistant

    Staff answers grounded in company documents.

  3. 03

    Document automation

    Extraction and classification feeding your systems.

  4. 04

    AI agent pilots to production

    Hardening prototypes with evaluation and guardrails.

Industries

Built for operational teams across industries

The patterns carry across sectors. What changes is the data, the systems and the rules, and we learn those first.

  • SaaS & technology

    Product engineering, integrations and AI features for software companies.

  • Professional services

    Automated intake, document workflows and client reporting for agencies, consultancies and firms.

  • Finance operations

    Invoice processing, reconciliation support and reporting automation.

  • Healthcare operations

    Scheduling, intake and back-office workflows, designed with privacy requirements in mind.

  • Education

    Admissions, learning platforms and administrative automation.

FAQ

Hire AI Engineers questions

Straight answers to the questions that come up in first calls.

Ask us directly
What does an AI engineer do that a regular developer does not?

An AI engineer designs features around language models: prompts, tools, retrieval, evaluation, cost control and safety. They still need strong software engineering skills to integrate those features reliably.

Do your AI engineers work in Python or TypeScript?

Both. We match the language to your existing stack.

Can an AI engineer help us decide what to build?

Yes, and for broader strategy our consulting service can help you prioritise AI opportunities before you add capacity.

Related services

Most engagements touch more than one discipline. The same team can take you from strategy to production.

01

Dedicated Teams

Vetted engineers who join your team, your tools and your delivery cadence.

  • Dedicated teams
  • Staff augmentation
  • Full-stack, AI & DevOps
  • Flexible scaling
02

Staff Augmentation

Add vetted engineers to your team, managed by you, scaled month to month.

  • Full-stack & front-end
  • Back-end & APIs
  • AI & automation
  • DevOps & cloud
03

Hire React Developers

Vetted React and Next.js developers who join your product team.

  • React & Next.js
  • TypeScript
  • Testing & performance
  • Design systems

Start a project

Tell us what is slowing your team down

Share the workflow, product or team challenge. We will come back with a clear recommendation and next steps.

Intro call · Fixed-scope proposal · No obligation