AI-native engineering hire
Hire generative AI engineers for text, image and audio products.
Find engineers with the depth your generation workflow needs, from model selection and adaptation to evaluation and delivery. Finalists have passed all agreed technical and soft-skill stages, with interest, compensation expectations and availability confirmed.
First qualifying finalist by business day 15, or stop the search for a full $2,000 refund. The search runs for 60 calendar days from the agreed launch date while the vacancy remains open.
Standard recruitment
Your search at a glance
Standard: 18% of first-year salary. $2,000 is paid at launch and credited toward that total; the balance is due when your hire starts. We agree the salary basis and search scope before payment.
60-day search, launch-payment refund and replacement terms
- Seniority
- Senior generative AI engineer searches; the technical bar is agreed in your brief.
- Compensation guide
- Indicative planning band: €64–104K a year in senior B2B contractor compensation across CEE.
- Search markets
- CEE candidates, with location and working-hour requirements agreed for your team.
Compensation is indicative. We agree the salary band, locations and working-hour overlap before search; the placement fee is separate.
Focus your engineers’ interview time
We assess technical and soft skills before introducing candidates, so your engineers meet people who have passed the agreed requirements. Review the evidence, run your own technical and team interviews, and choose who to hire. We support coordination and the offer process.
Choosing the role
Make the generative AI brief specific
Generative AI covers products that create text, images, audio or other outputs. The title alone does not establish the expertise you need. An image-editing workflow, a voice interface and a document-drafting feature have different quality criteria and operating constraints. Start by naming the output, the user task and the engineer’s responsibilities.
A senior hire might own provider selection, model adaptation, application integration and the evaluation process. Depth in one relevant modality can be more useful than superficial experience across three. We include additional modalities when they are part of the funded scope, and distinguish model-training work from product engineering around existing models.
Quality needs a definition your team can use. An image product may prioritise instruction adherence and editable outputs; a voice product may prioritise intelligibility and response timing; a drafting feature may prioritise factual support and reviewability. The candidate should be able to design an evaluation with your domain reviewers and explain which errors remain acceptable.
Bring to the intake: representative inputs and outputs, the modalities in scope, user interaction requirements, existing providers, available data and deployment constraints. For language-model application work, compare our LLM engineers. For a role spanning predictive modelling and generative features, compare AI/ML engineers.
Across Recruo searches
Our recruitment results so far
Company-wide observations reported by Recruo’s founder on 11 September 2026. These describe our overall experience, rather than a separate cohort for this role or region.
- Pass every client assessment stage
≈9/10
Presented candidates who successfully pass the client’s full assessment process, including technical interviews.
- Candidates the client would offer to
≈4/5
Client willingness to make an offer after assessment. Offers sent, accepted and hires are separate outcomes.
- Completed probation periods passed
100%
All placed candidates whose probation has concluded have passed so far. Ongoing probation periods are excluded.
How to read these results
Pass every client assessment stage: Candidates who pass all client assessment stages, relative to candidates presented. Around 9 in 10 is an approximate company-wide observation, not a published sample of exactly ten people. Offers, acceptance and starts are separate outcomes; sample size, reporting period and treatment of ongoing assessments are not yet published.
Candidates the client would offer to: Presented candidates the client considers suitable for an offer, divided by candidates presented. Around 4 in 5 describes willingness to offer; it does not mean four offers or hires for every five candidates.
Completed probation periods passed: Placed candidates who passed probation, divided by placements whose probation period has ended. Probation lengths vary by engagement; this is not a 90-day retention measure or a guarantee of future outcomes.
Sample sizes and the reporting period are not yet published. The candidate ratios are approximate; none of these results is a forecast for your vacancy.
Example scorecard
Evidence to look for in your shortlist
Illustrative assessment criteria, not a candidate profile or a record of a completed placement. The final scorecard is agreed for your role.
Example scorecard: senior generative AI engineer
Role scope: Use this scorecard to assess whether a candidate can deliver the generation workflow you need and explain its quality and operating tradeoffs.
- Modality fit: demonstrates depth in the text, image or audio responsibilities the brief actually requires.
- Model decisions: can compare a hosted service, an existing open model and adaptation against the same use case.
- Quality evaluation: defines useful output criteria and works with domain reviewers on ambiguous examples.
- Product integration: understands how generation time, failures and review steps affect the user experience.
- Delivery constraints: considers data access, provider limitations, operating costs and the review needed before release.
How we source
How we assess generative AI experience
We source against the actual modality and responsibility: model adaptation, generation pipelines, real-time product integration or a combination. Relevant experience may come from applied ML, computer vision, speech engineering or product development. We do not require a specific career start date, a public model or experience in unrelated modalities.
The technical screen asks candidates to explain an implemented generation workflow, the alternatives they considered and how they judged output quality. For image work, follow-ups can explore controllability and the cost of generation. For audio, they can explore streaming behaviour, interruption and failure handling. For adaptation work, they can explore data suitability and evaluation against a baseline. A human recruiter reviews the AI-supported interview before shortlist delivery.
Public work is one source of evidence; confidential architecture walkthroughs, redacted examples and agreed work samples are also valid. We document the candidate’s personal contribution, relevant depth and areas needing further review. Your team can then focus its interview on the generation workflow it intends to build.
Role-specific screening
What we assess
The useful distinction is depth in your required modality and workflow. We narrow the broad title into concrete responsibilities before sourcing.
Modality depth
Experience relevant to your outputs
Role-specific screening criteria agreed during intake
Output quality
Useful criteria and evaluation evidence
Role-specific screening criteria agreed during intake
Product operation
Latency, failure handling and cost
Role-specific screening criteria agreed during intake
A candidate does not need every generation modality to be a strong hire. We show the match to the immediate scope and distinguish demonstrated experience from capabilities that still need assessment.
FAQ
Frequently asked questions
Get started
Tell us about your open role
Share your generative AI engineer brief. We agree the assessment criteria, budget, launch date and 60-day search scope before you commit.
$2,000 to launch
Fully credited toward the 18% Standard fee
90-day guarantee
One replacement search under agreed conditions
Human review
Recruiters review the screening evidence
Also on Recruo
Roles we hire for
Hire by location
Compared to other agencies
Further reading
Hire in the UK