Lehire for Technology

Hire engineers on evidence, not keyword luck

Every resume says React, AWS, and impact. Lehire scores each candidate against your actual role rubric, captures what your panel really thought, and turns five strong finalists into one defensible decision.

Demo led onboarding. We run Lehire on your own roles and resumes before you subscribe.

Decision Engine
Ranked shortlistSenior Backend Engineer
1PSPriya SharmaSenior Backend Engineer93Hire
2DCDaniel ChoSenior Backend Engineer87Strong consider
3ATAlex TorresSenior Backend Engineer64Waitlist
Evidence attached to every score
One rubric
per role, applied to every candidate
0 to 100
evidence backed fit scores with reasoning
200 resumes
evaluated per batch, in minutes
Every decision
documented and remembered
The problem

Where technology hiring actually breaks

Tech hiring fails at the decision, not the pipeline. You can source hundreds of candidates and still pick wrong, because the evaluation is inconsistent.

Keyword stuffed resumes all look identical

Every applicant lists the same stack. Skimming cannot tell you who actually shipped with it and who sat near it.

Evidence backed fit scores

Lehire reads the whole resume against your rubric and returns a 0 to 100 score with the reasoning written out, so you see why someone scored 86 and not just that they did.

Every interviewer measures a different bar

One panelist grills system design, another chats culture. Debriefs become opinion contests won by the loudest voice.

Structured scorecards on one rubric

Everyone evaluates the same criteria for the role. Interview signal lands in the same scorecard, so the debrief compares evidence instead of impressions.

Two strong finalists, zero defensible tiebreaker

When it is close, teams default to gut feel or recency. Six months later nobody can explain why the offer went where it did.

Decision Engine ranking

Resume fit, interview scores, and role criteria combine into one ranked shortlist with the tradeoffs spelled out. The decision comes with its own paper trail.

How it works

Decision intelligence for technology, in three moves

01

Define the bar once

Paste the JD or generate one with AI. The role rubric becomes the single standard every engineer is measured against, from first screen to final debrief.

02

Score every candidate the same way

Upload up to 200 resumes per batch. Each candidate gets an evidence backed fit score against your rubric, with the reasoning visible, in minutes.

03

Decide between the finalists

Interview scorecards and AI fit roll into one ranked comparison. You choose between candidates with evidence, and Lehire remembers the decision for next time.

Built for your roles

Everything between screening and the offer

Backend EngineerFrontend EngineerFull StackDevOps / SREData EngineerEngineering ManagerQA EngineerProduct Manager

AI fit scoring with reasoning

Not a keyword match. Each engineer is scored against your role rubric with written rationale you can challenge or confirm.

Interview scorecards

Panel feedback captured on the same criteria, so system design signal and culture signal are comparable across interviewers.

Decision Engine

Ranks finalists by combined resume fit and interview evidence. The tiebreaker is structured, not the loudest voice in the debrief.

Hiring memory

Silver medalists from your last backend search resurface automatically when the next role opens. No re uploading, no cold start.

AI JD generator

A precise rubric starts with a precise role. Generate the description, LinkedIn post, and outreach from a few details.

Talent pool search

Every candidate you have ever evaluated is searchable and re scoreable against new roles, with their history attached.

Technology teams ask us

Does Lehire replace our ATS?+

No. Keep your ATS for tracking and compliance. Lehire is the decision layer on top: structured evaluation, interview intelligence, and hiring memory for the candidates already in your process.

Can it evaluate niche technical stacks?+

Yes. The rubric comes from your job description, so a Rust systems role and a React product role are scored on different criteria. You can also adjust criteria weighting per role.

How does it handle take homes and technical interviews?+

Interview scorecards capture structured feedback from any round, including technical screens and take home reviews. That signal feeds the final ranking next to resume fit.

We get hundreds of applicants per posting. Does it scale?+

Premium scores up to 200 resumes per batch and includes 1,500 AI actions per month. High volume teams move to Enterprise with unlimited credits.

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Your next engineering hire deserves more than a gut call

Book a personalised demo and we will run Lehire on your own technology roles and real resumes.