Hire AI
Engineers
Bring on AI engineers who build retrieval and agent systems that survive real users, not just a convincing demo. Grounding that stops the model inventing answers, retrieval that finds the right context, and the evaluation loop that proves it. Dedicated to your product or embedded in your team.
Talk to our team→
Why teams hire AI engineers from us
Production, not demos
Retrieval quality, grounding, latency and cost under load, and a real evaluation loop. The layer under the agent that decides whether it ships.
Software engineers first
What they build is a maintainable, deployable service with observability, not a notebook nobody else can run. Designers, QA, and reviewers behind every engineer.
Read the code before you hire
A published teardown of our production hybrid RAG and public multi-agent repos on GitHub. You can read how we build before you commit.
The stack
Skills our AI engineers bring
Fluent across the production AI stack: retrieval, agents, and the evaluation layer that keeps them honest.
How it works
How hiring works
From the first call to an engineer in your standup, usually inside two weeks.
A short call to understand your product, your data, and where AI actually earns its place in it.
We propose vetted AI engineers who fit your stack and timezone, with the public teardown and repos for you to review.
Talk to the engineers, check the fit, and choose who joins. You make the call, not us.
Your engineer joins your standups and tools, managed by you, backed by our designers, QA, and reviewers.
Engagement models
Work with us how you need
Pick the model that fits your stage. You can change it as your roadmap changes.
Dedicated engineer
One senior AI engineer, full-time on your product and managed by you. Best for an ongoing AI roadmap.
Dedicated team
A cross-functional pod of engineers, design, and QA, ready to ship an AI feature end to end without growing headcount.
Project-based
A scoped build delivered end to end against a fixed plan, price, and timeline.
Build vs buy
Why a dedicated team beats the alternatives
How hiring senior AI engineers through us compares to building in-house or going freelance.
Put senior AI engineers on your product this month. Tell us what you're building.
Proof
Read the work before you hire
A full production write-up: hybrid retrieval, grounding, and the eval loop that keeps it honest.
Real agent code on GitHub. Read how our engineers build before you commit.
Our AI coach ships inside Stepler, Sweden's #1 fitness app.
Questions
Hiring AI engineers, answered
What AI work has your team actually shipped?
Production retrieval and agent systems. We published a full teardown of our hybrid RAG on Qdrant, including the grounding and evaluation work, and we maintain public multi-agent repositories you can read.
Do you build RAG, agents, or both?
Both. Retrieval is the layer under most useful agents, so we treat them together: grounded retrieval first, then the agent that reasons over it.
How do you keep the model from hallucinating?
Grounding and evaluation. We constrain answers to retrieved, cited context and run an evaluation harness with golden sets, so a change that increases hallucination shows up before your users find it.
Which models do you use?
OpenAI and Anthropic families behind a provider-agnostic layer, so you are not locked to one vendor and can route by cost and capability.
Can I hire one engineer or a team?
Both, sized to your stage. One senior AI engineer embedded with your team, or a cross-functional pod that ships the feature end to end.
Ready to add senior AI
engineers to your team?
Tell us what you're building and we'll match you with the right people.
Talk to our team→CONTACT OUR TEAM
Our team contacts you within 24 business hours
We collect all the key requirements from you
The team of developers prepares estimation
We can sign NDA since we respect the confidentiality of our clients