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How we help you hire

How the Recruo recruitment flow works.

Your engineers spend their interview time on candidates who have already passed the technical and soft-skill assessments agreed for your role. We handle sourcing and assessment, share the evidence, and support your own interviews and offer process through to hire.

The Standard recruitment flow

  1. 0

    Intake call

    Human (AM)

    30-min scoping call. We capture the JD, must-haves, culture, budget, timeline.

    Output: Signed mandate

  2. 1

    Sourcing

    Recruiter

    LinkedIn Recruiter, direct outreach, and regional networks across Europe (DOU, Djinni, Just Join IT), Latin America and North America — plus our private candidate network.

    Output: A role-specific candidate pool

  3. 2

    AI CV screening

    AI

    Every CV scored against the JD. Only 70+ scores move forward.

    Output: Candidates selected for interviews

  4. 3

    Soft-skills interview

    Recruiter

    20–30 min call: motivation, culture fit, salary, English, availability.

    Output: Structured notes

  5. 4

    AI technical interview

    AI Agent

    AI-conducted technical interview on video with adaptive follow-ups and anti-cheat checks — up to the fully locked-down Recruo Secure Browser. Every result is reviewed by a human recruiter.

    Output: Hard-skills report + score

  6. 5

    Finalists and hiring support

    Human + AI

    Meet candidates who passed the agreed assessments, with expectations and availability confirmed. Your team runs its own technical and team interviews; we support the process through to hire.

    Output: Assessed finalists and continued support

See a full scorecard example

Standard · Sample deliverable

See the assessment before you spend interview time.

Review the technical evidence, candidate answers and recruiter judgment behind the recommendation before you book an interview.

This composite Senior LLM Engineer profile illustrates the report format; it is not a record of one individual candidate. For this example role, RAG, retrieval, evaluation and inference are required; fintech experience, multimodal pipelines, diffusion models and GPU kernel tuning are optional.

Sample recommendation

Advance to client interview

The candidate passes this example role’s required RAG, retrieval, evaluation and inference assessments. Recruiter notes confirm motivation, availability and salary alignment. Fintech and multimodal experience are optional gaps. Your team can use this evidence to plan its own technical and team interviews.

AI Technical Assessment

Candidate A
4 questions · 20–30 min interview
85%

Overall AI Score

SENIOR-LEVEL DEPTH

Average 8.5/10 across RAG, retrieval, evals and inference

1
RAG Architecture

Design a RAG system over a 2M-document knowledge base

9/10

Excellent architecture covering chunking strategy, hybrid retrieval, and context-window budgeting.

Takeaway: Production-ready thinking on retrieval quality, latency, and cost tradeoffs.

2
Vector Search

Tune retrieval quality: hybrid search, reranking, recall@k

9/10

Comprehensive tuning approach: BM25 + dense hybrid, cross-encoder reranking, recall@k tracking.

Takeaway: Real production retrieval experience — not just framework defaults.

3
Eval Design

Design an eval suite for an open-ended generation task

8/10

Solid LLM-as-judge design with human-rater calibration and regression gates in CI.

Takeaway: Treats evals as engineering infrastructure, not a one-off benchmark.

4
Inference & Cost

Cut p95 latency and cost of a production inference stack

8/10

Walked through a real incident: 1.2s p95 cut to 220ms via speculative decoding and prompt slimming.

Takeaway: Aware of the cost-quality-latency triangle, not just the happy path.

Each candidate gets the full per-question report — answers, evaluations, takeaways.

See a full scorecard

Explore the full sample shortlist PDF

A redacted shortlist PDF, available here after you submit. We use your email to respond to this request.

AI skills & interview integrity

Assess the skills. Review the signals.

Anti-cheating signals help our recruiters investigate concerns before candidate introductions. For roles that use AI tools, an optional coding assessment also examines how candidates work with them.

AI changes the skills worth assessing

GitHub Copilot, Cursor, ChatGPT — AI-assisted development is the default. But most hiring pipelines still test for pre-AI skills only.

AI proficiency ≠ copy-pasting prompts

The best engineers know when to use AI, when to override it, and how to validate its output. That judgment is what the assessment should make visible.

Bad AI habits cost more than no AI at all

Blindly trusting AI-generated code leads to security vulnerabilities, hallucinated logic, and tech debt that compounds silently for months.

AI-assisted coding assessment

An optional module added to the included technical assessment: real coding tasks with AI tools available, followed by probing questions about the candidate's AI-assisted workflow. The result is a separate AI Proficiency Score alongside the standard technical evaluation.

How it works

The candidate gets access to Copilot/Cursor during part of the interview. We observe how they prompt, validate, and iterate — then score their AI fluency on a structured rubric.

AI-assisted coding

Can they use Copilot/Cursor effectively while catching errors?

Prompt engineering

Do they write precise prompts, or do they brute-force trial and error?

AI output validation

Can they spot when an LLM hallucinates, introduces a vulnerability, or produces subtly wrong logic?

AI-native architecture

Do they know when to reach for an LLM vs. a deterministic solution?

Recruo Secure Browser

Our interview environment adds controls and session-integrity signals to support review. The available controls depend on the setup; no browser can prove that outside assistance was impossible.

Why it matters in 2026

A polished answer does not establish practical experience. Adaptive follow-ups and evidence review help recruiters understand how the candidate reasons and which claims need clarification.

Locked browser session

Ask which browser controls are supported in the agreed interview setup.

Copy-paste detection

Available session signals can highlight material that needs follow-up.

Recruiter follow-up

Concerns are reviewed in context, with clarification from the candidate where needed.

Evidence and context

Review the answers and session evidence together; a flag does not prove external assistance.

Assessment options are scoped around the role. Available as add-ons for Standard searches. For Executive Search, the leadership assessment format is agreed privately with sales.

Most used when hiring LLM engineers, RAG engineers, Evals engineers, ML platform engineers, Agentic AI developers, Generative AI engineers or AI/ML engineers.

EU AI Act

Aligned by design, not bolted on.

Employment is one of the AI Act's high-risk areas. Recruo combines AI assessment evidence with recruiter review. Confirm the applicable controls and documentation for your engagement. Your responsibilities as employer or deployer remain.

AI recommends; a human recruiter reviews and owns each shortlist decision. The scorecard gives your team evidence to discuss. Data handling, notices and the review process should be agreed before the search starts.

Review the scope before you start

Candidate notification of AI use before assessment.

Traceable scorecard and recruiter sign-off for every shortlisted candidate.

Assessment evidence and review responsibilities agreed for the workflow.

Human review and escalation path for contested assessments.

Retention, deletion and audit-log terms confirmed per engagement.

Recruiter review before shortlist handoff.

Full security & GDPR posture

EU AI Act Rollout

Feb 2025

Prohibited AI practices ban

Aug 2025

GPAI + governance obligations

Dec 2027

Next

High-risk AI rules for employment

current timeline following the AI Omnibus agreement

Aug 2028

High-risk AI embedded in regulated products

Human oversight in practice

A recruiter reviews shortlist evidence. Agree the documentation and handoff responsibilities that your team needs for this workflow.

The 2027 timeline does not pause GDPR or existing employment and equality obligations — those apply to AI screening today.

Official EU implementation timeline ↗

Platform access

Want Recruo evaluation inside your own hiring system?

The same AI technical interview, secure browser, and structured scorecard can be discussed as private API or MCP partner access for ATS, marketplace, agency, and internal hiring workflows.

AI technical interview API

Trigger evaluations from an ATS or hiring platform and receive scorecard output through API and webhook patterns.

Explore API access

Recruiting MCP server

Expose candidate evaluation, status checks, scorecard retrieval, and audit evidence to internal hiring agents.

Explore MCP access

Get started

Tell us the role.
We'll help plan your next step.

Add whatever you know about the role, stack and hiring timeline. Your name and work email are enough to start; we'll reply within 24 hours.

$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

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