Trusted by teams at Satellogic

See talent clearly.

Hiring is the highest-stakes call most teams make with the least structure. Messa replaces the guesswork with structure and evidence, so every hire is as sharp as your best one. The decision stays yours.

See how it works
Messa hiring pipeline: prepare, interview, decide

The Problem

Great hiring becomes occasional hiring.

Your team knows how to hire well. They just can't do it for every role, every panel, every time.

Shortlisting needs criteria.

Most teams skim and hope.

Interviews need preparation.

Most don’t get it.

Panels need coordination.

Most don’t have it.

Scorecards need discipline.

Most skip it.

So conversations with candidates become missed opportunities. Three interviewers ask the same three questions. Candidates are evaluated against different bars. Decisions come down to memory and gut.

Your stack tracks the process. Nothing helps you make the right hire.

0+
Applications per role
Most never get read
Source: Ashby Talent Trends Report, 2026
0x
More predictive
Structured vs. unstructured interviews
Source: Sackett et al., J. Applied Psychology (2022)
0%
Of failed hires
Showed warning signs the interviewer ignored
Source: Leadership IQ

Messa

AI-scored shortlist in seconds
Custom interview guide for every interviewer, built from the role and the candidate's background
Sidekick guides every conversation in real time
Per-skillset scorecard, pre-filled from the conversation. Edit, never start from scratch
Private coaching after every interview: where you spent time, what you missed, what to sharpen

Traditional

Scroll through 200 CVs hoping for the best
Generic prep, same questions across the panel
Notetaker captures the call, doesn't help during the interview
Blank scorecard 30 min after the call, if it gets filled at all
No feedback on your interviewing. Same blind spots, every time

Your company DNA, the role's real requirements, every candidate's profile, threaded through every step. One system from shortlist to coaching, so nothing gets lost between handoffs.

The part nobody built.

Your stack is full. Your hiring is still guesswork. Messa is the missing piece.

How It Works

Step 1 sets the bar. Every other step enforces it.

That's why it's a system, not four features duct-taped together.

AllSystem DesignLeadershipPrototypingUser ResearchDesign Systems
Charly Chaves
charly@coderhouse.com
68% fit
Martina C.
martina@docfav.com
48% fit
Ankrit Seth
aseth@sentra.xyz
45% fit
Pablo Armentano
pablo@uink.digital
75% fit
Maya Reyes
maya@reyes.studio
75% fit
Sarah Chen
sarah.chen@linear.app
92% fit
Marcus Johnson
marcus@basecamp.com
87% fit
Priya Patel
priya.patel@stripe.com
81% fit
James Wilson
jwilson@notion.so
74% fit
Emma Thompson
emma@netlify.com
64% fit
David Kim
david.kim@shopify.com
58% fit
Ana García
ana.garcia@mercury.com
71% fit
Tom Fischer
tom.fischer@airbnb.com
66% fit
Lisa Wang
lisa.wang@plaid.com
83% fit
Omar Hassan
omar@datadog.com
55% fit
Camila Ruiz
camila.ruiz@ramp.com
79% fit
Raj Mehta
raj@coinbase.com
62% fit
Sophie Laurent
sophie@figma.com
88% fit
Luca Bianchi
luca@twilio.com
43% fit
Nina Petrov
nina.p@hashicorp.com
77% fit
Maya Reyes
Senior Product Designer
Pre-Interview Fit0%
Resume AnalysisInterview GuideInterviewsScorecard
Resume uploaded. Click analyze to begin.Analyze Resume →
Interview Sidekick
11:22 AM
···
Maya
01:39
RecTranscript
Maya Reyes·View Profile
Senior Product Designer
Introduction5 min
Introduce yourself and the company stage
Set expectations for the conversation
Ask for a brief overview of recent work
What attracted you to this role specifically?
Recent Wins15 min
Walk me through a recent product you shipped that you're most proud of
When timelines were tight, what trade-offs did you personally make?
Tell me about a time you elevated the quality of a complex workflow
How did you measure success for that project?
What was the most unexpected challenge you faced during delivery?
Overcoming Challenges15 min
Tell me about a project where you missed a target or had to cut scope
When you faced strong pushback on a design direction, how did you handle it?
Describe a moment when you delivered under significant ambiguity
How do you prioritize when everything feels urgent?
Tell me about a time you had to say no to a stakeholder
Scale & Impact10 min
Walk me through a time you created or evolved a design system
Describe an example where you scaled something across teams
How do you ensure consistency when multiple designers work in parallel?
What's your approach to documentation and handoff at scale?
Live Assist Follow UpInterview CoachFinish
Maya Reyes
Senior Product Designer
After InterviewStrong Hire
Pre-Interview Fit75%
Resume AnalysisInterview GuideInterviewsScorecard
Interview with Maya Reyes
Your DecisionStrong Hire
Overall Assessment

Maya demonstrated a strong command of end-to-end product design execution throughout the interview. Her work at Carbon Direct and Pachama showed consistent ability to take ambiguous problems and ship high-quality solutions under tight timelines. She articulated clear trade-offs she made in her design decisions, backed by measurable outcomes like reduced onboarding time and improved data clarity in complex environmental dashboards.

Pros
Exceptional execution speed with evidence of shipping complex data products in compressed timelines
Strong systems thinking — built reusable pattern libraries that measurably improved team velocity
Effective cross-functional collaborator who navigates disagreements with data and prototypes
Cons
Limited experience in consumer-facing products — all recent work is B2B/enterprise
Could go deeper on accessibility practices and inclusive design methodology
Step 01

Know what to look for

Messa analyzes the role and suggests the skill sets that matter, the questions that reveal them, and how to split focus across interviewers. Your team walks in with a plan, not a blank page.

Step 02

Shortlist with confidence

Messa reads the job description and distills the criteria. Your team approves. Every application scored against those criteria, with reasoning. Your team decides who moves forward.

Step 03

Stay sharp in the conversation

Sidekick knows the candidate's profile and what your team is assessing, surfacing the right questions and follow-ups the moment they matter. The interviewers stay in control. Nothing important slips by.

Step 04

Decide with evidence

Your team makes the call. Messa drafts the scorecard from the conversation, grounded in evidence. Everyone decides from the same facts. Not impressions. Not vibes.

Compounding

Every hire sharpensthe next one.

Most hiring resets to zero every time. Same debates, same blank page, same gut calls. Messa keeps the bar. Every role you run and every scorecard you write makes your team's judgment sharper, not just faster.

Works with your existing stack

Messa plugs into Greenhouse, Ashby, BambooHR, Lever, and more. No migration. No switching costs.

Greenhouse
Ashby
BambooHR
Lever
LinkedIn
Workable
Google Meet
Zoom
Greenhouse
Ashby
BambooHR
Lever
LinkedIn
Workable
Google Meet
Zoom

The Product

Built into the workflow, not bolted on.

Software paired with a methodology built by recruiting experts, and a partner who helps your team apply it.
Messa doesn't hand you a blank template. It shows up with the answers.

Search...K

Shortlisting results for “Junior AI Software Engineer”

Showing classified candidates from the latest evaluation.Apr 24, 2026 4:27 PM

Candidate funnel280 evaluated
15
53
212
Strong fit (15) Maybe (53) Low fit (212)
EN
Ervenst NoelStrong fit
Full Stack Developer at Soundscope
Ervenst demonstrates proficiency in AI integration and full-stack development, with shipped LLM-backed features and clear evidence of production SQL.
78%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
AM
Ateef MahmudStrong fit
Co-Founder & CTO at Synari
Ateef brings strong AI and API development skills with a focus on quantum computing; lacks long-term professional experience but shows compounding ownership.
74%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
MR
Maya ReyesStrong fitClick me
Senior Product Designer at Carbon Direct
Maya pairs a strong product-design portfolio with hands-on AI tooling work — fast shipper, clear communicator, leans on systems thinking.
72%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
KS
Kummari Sai KumarMaybe
Machine Learning Intern at Verzeo
Sai is technically proficient in AI and Python, with strong project experience, but lacks direct API development and React UI exposure crucial for the role.
68%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
AF
Agustin FigueroaMaybe
Software Developer (AI Engineering) at CORADIR S.A
A promising AI engineer with solid backend and AI skills, but lacks documented side projects or React experience for a full-stack role.
67%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
PR
Prateek RankaMaybe
Fullstack Developer & Researcher at USC Information Sciences Institute
Prateek shows solid AI and software engineering skills through academic projects, but his short job tenures may impact readiness for fast-paced roles.
66%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
RR
Ramesh RavulaMaybe
Python Full Stack Developer at BCBS
Experienced Python developer with strong AI integration skills; may be overqualified for junior role's exploratory focus.
65%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
CC
Charly ChavesMaybe
Backend Engineer at Coderhouse
Charly's backend foundations are solid but AI exposure is limited to coursework — would need ramp time on the model layer.
64%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
ET
Emma ThompsonMaybe
Frontend Engineer at Netlify
Strong React fundamentals and a track record on developer-tools UIs; AI/ML background is thin and self-taught.
63%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
TF
Tom FischerMaybe
Software Engineer II at Airbnb
Reliable shipper at scale, good systems intuition; portfolio doesn't yet show greenfield AI work.
62%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
SC
Sarah ChenMaybe
Software Engineer at Linear
Sarah brings developer-tools polish and strong async collaboration; AI exposure is via internal LLM tooling rather than shipped product.
61%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
MJ
Marcus JohnsonMaybe
Senior Engineer at Basecamp
Marcus is a calm, opinionated builder; less depth on the model side but strong engineering fundamentals would translate quickly.
60%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
DK
David KimMaybe
Software Engineer at Shopify
Generalist engineer with e-commerce depth; AI familiarity limited to LLM-prompting on internal tools.
59%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
PP
Priya PatelMaybe
Backend Engineer at Stripe
Priya has strong distributed-systems chops; AI experience is mostly through internal Stripe ML tooling and would need to be assessed live.
59%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
JW
James WilsonMaybe
Senior Frontend Engineer at Notion
James ships highly polished UI; needs assessment on whether his backend AI integration depth matches the role's full-stack expectation.
58%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
OH
Omar HassanMaybe
Backend Developer at Datadog
Strong on distributed systems and observability; AI exposure mostly through OSS contributions.
57%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
AG
Ana GarcíaMaybe
Full Stack Engineer at Mercury
Ana ships fast in fintech UI; AI work limited to internal copilots — needs an interview to gauge depth on the model layer.
57%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
RM
Raj MehtaMaybe
Software Engineer at Coinbase
Solid CS fundamentals and typescript depth; ML coursework but no shipped AI features.
56%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
LW
Lisa WangMaybe
Engineer at Plaid
Lisa has strong API design instincts; her AI involvement is consultative rather than hands-on building.
55%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
NP
Nina PetrovMaybe
Senior Software Engineer at HashiCorp
Nina brings infra depth and reliability mindset; AI exposure is through OSS tooling rather than product features.
54%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
CR
Camila RuizMaybe
Full Stack Engineer at Ramp
Camila ships polished UI quickly; AI/ML experience limited to a hackathon project — may need mentorship on production model integration.
53%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
SL
Sophie LaurentMaybe
Product Engineer at Figma
Sophie's design-engineering depth is rare; AI side is a stretch and would likely require pairing in the first months.
53%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
TF
Tomás FerreiraMaybe
Backend Developer at Nubank
Tomás knows the JVM and event-driven systems cold; AI exposure is greenfield — strong engineer who could grow into the role.
52%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
MI
Maya IyerMaybe
Software Engineer at Cloudflare
Maya brings edge-runtime depth; her AI exposure is mostly through Workers AI bindings — solid but narrow.
51%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
FC
Felipe CostaMaybe
Engineer at Loft
Felipe ships product features at pace; AI work is limited to chat-style integrations and not deep enough yet for the role.
51%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
DP
Daniel ParkLow fit
Mobile Developer at Robinhood
Daniel's strengths are mobile-native; AI integration depth is limited and not shipped to production.
49%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
IR
Isabella RossiLow fit
Frontend Engineer at Spotify
Strong UI engineering background; AI/ML resume is sparse and reads as exploratory rather than hands-on.
48%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
LB
Luca BianchiLow fit
Junior Developer at Twilio
Early-career engineer with limited project breadth; AI exposure is purely tutorial-level at this stage.
47%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
HT
Hiroshi TanakaLow fit
Backend Engineer at Mercari
Hiroshi's backend skills are strong, but his portfolio doesn't show AI-feature delivery.
46%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
OB
Olivia BrownLow fit
Junior Engineer at Klaviyo
Olivia is early-career with strong fundamentals; AI exposure remains coursework-level.
45%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
SP
Santiago PérezLow fit
Frontend Developer at Mercado Libre
Santiago ships clean React UI; AI integration appears only via AWS managed services, not custom model work.
45%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
AK
Aisha KhanLow fit
Software Engineer at Pinterest
Aisha is a steady contributor on internal tools; AI exposure is light and feature-flagged at best.
44%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
LM
Leo MartinezLow fit
Junior Developer at Rappi
Leo has 1.5 years on a small product team; AI experience is a single side project that wasn't shipped.
43%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
MA
Mia AnderssonLow fit
Backend Engineer at Klarna
Mia's resume reads as fintech-focused; AI integration depth is shallow and tooling-level.
43%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
CM
Carlos MendozaLow fit
Software Engineer at Globant
Carlos has consultancy experience across stacks; AI work is tutorial-grade and not productionised.
42%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
RS
Rebecca StoneLow fit
Engineer at Twilio
Rebecca knows messaging infra well; AI exposure limited to internal hackathons.
41%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
YS
Yuki SatoLow fit
Junior Engineer at LINE
Yuki has strong mobile JS depth; lack of AI portfolio makes this a stretch for the role.
40%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
MS
Mateo SilvaLow fit
Software Engineer at PedidosYa
Mateo ships product features at a steady pace; AI integration appears only via 3rd-party SDKs.
39%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
CD
Chloe DupontLow fit
Frontend Engineer at BlaBlaCar
Chloe's frontend craft is good; AI work isn't represented in any shipped feature.
38%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
AR
Arjun ReddyLow fit
Software Engineer at Razorpay
Arjun has solid fintech systems experience; AI/ML work absent from his portfolio.
37%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
SM
Sofia MüllerLow fit
Junior Engineer at N26
Sofia is early-career; AI exposure consists of one bootcamp module.
36%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
PA
Pedro AlmeidaLow fit
Software Engineer at iFood
Pedro brings high-throughput backend depth; the AI side of the role isn't reflected in his resume.
35%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
HK
Hannah KimLow fit
Frontend Engineer at Toss
Hannah's React/Next fluency is strong; AI exposure isn't visible beyond tutorial demos.
34%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
DR
Diego RamirezLow fit
Junior Developer at Belvo
Diego has 1 year of professional experience; not yet at the bar for the role's AI expectations.
32%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
EN
Eva NilssonLow fit
Software Engineer at Bolt
Eva's mobility-platform experience is interesting; AI work is absent from her trajectory.
30%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
KW
Kai WongLow fit
Backend Engineer at Sea Limited
Kai's strengths are SEA marketplace systems; AI integration isn't part of his recent work.
28%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
JB
Julia BeckerLow fit
Junior Engineer at GetYourGuide
Julia is early-career and the AI dimension of the role isn't represented in her work history.
25%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
AV
Andrei VolkovLow fit
QA Engineer at JetBrains
Andrei's strengths are in test automation; software-engineering depth and AI experience are both light.
24%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
ML
Mei LinLow fit
Frontend Developer at Tencent
Mei has strong CSS instincts; backend and AI dimensions of the role are absent from her resume.
23%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
GS
Gabriel SouzaLow fit
Junior Backend Engineer at Dock
Gabriel is in his first role; AI familiarity is at the tutorial level only.
22%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
ZA
Zara AhmedLow fit
Mobile Developer at Careem
Zara's portfolio is mobile-first; web and AI sides of the role aren't reflected in her work.
21%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
NH
Niklas HoffmannLow fit
Junior Engineer at Trade Republic
Niklas is early-career on a fintech dashboard team; no AI work and limited backend depth.
20%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
PL
Priscila LimaLow fit
Frontend Engineer at Quinto Andar
Priscila's strengths are in real-estate UX; the AI engineering bar is a stretch.
19%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
RS
Ravi SharmaLow fit
Junior Developer at Swiggy
Ravi has 8 months on a delivery-app team; AI work is absent from his trajectory.
18%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
LB
Linnea BergLow fit
Software Engineer Intern at Spotify
Linnea is currently interning; not yet at the bar for a junior full-time role with AI focus.
17%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
JP
Joon-ho ParkLow fit
Junior Backend Engineer at Coupang
Joon-ho's recent work is on internal admin tooling; AI exposure isn't represented.
16%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
HC
Helena CostaLow fit
Junior Frontend Developer at OLX
Helena is six months into her first role; AI/ML side of the role is well outside her current scope.
15%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
BV
Bruno VargasLow fit
Junior Software Engineer at Despegar
Bruno's experience is travel-platform UI; AI work is absent and the engineering bar is light.
14%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
NH
Nadia HakimLow fit
Frontend Intern at Careem
Nadia is an intern with limited shipped product experience; the role is a stretch on multiple dimensions.
13%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
EL
Erik LindqvistLow fit
Junior Developer at Klarna
Erik has 6 months on a payments admin team; AI exposure is absent from his work.
12%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.
CV
Camila VidalLow fit
Frontend Engineer Intern at Mercado Libre
Camila is interning on a UI team; both senior engineering bar and AI dimension are out of reach for now.
11%
Green flags
  • Experience with FastAPI and AI integrations.
  • Hands-on experience with microservices architecture.
Red flags
  • No evidence of React UI experience.
  • Short professional tenure in relevant roles.

Underneath the workflow

The features you can see are the surface. These are the decisions underneath them.

0m · the surface
01
−1m

Criteria built per role

Messa works out what each role actually needs before anyone gets scored. Seniority at a Series A isn't seniority at a Fortune 500.

02
−2m

Nothing it can't point to

Every score traces back to a specific line in the candidate's own material. Messa won't make a claim it can't source.

03
−3m

Same shape every time

Every evaluation comes out in the same structure, never loose text. A whole search stays comparable, whoever ran the interview.

04
−4m

Catches the fakes

Messa screens for fabricated applications: timelines that don't add up, phrasing repeated across unrelated candidates, credentials that fall apart on a second look.

05
−5m

Reads words, not faces

Never voice, face, or expression. Just what a candidate said and wrote. Reading competence off tone is a known way to smuggle in bias.

06
−6m

Gets sharper as you go

Every interview and outcome gets linked back to who actually worked out. A chatbot forgets the second it ends. Messa keeps all of them to sharpen the next call. The one piece that compounds.

What Teams Say

Trusted by hiring teams.

"With Messa, I went from scrambling to summarize interviews to submitting scorecards in minutes... with actual evidence to back every decision and alignment."

Mercedes Foster
People Manager, TiendaMia
TiendaMia

"Every conversation feels more structured with Sidekick, and the follow-up suggestions consistently improve our interviews."

Alex Merutka
CEO, Craftsman+
Craftsman+

"After using Messa regularly, it's hard to believe we could go back to what we were doing before. This is a gamechanger for efficiency and consistency in the hiring process."

Emiliano Kargieman
CEO, Satellogic
Satellogic

"Interviews feel more natural with Messa. It frees me up to focus on the candidate, then gives us a fast, detailed wrap up that helps improve the recruiting process."

Diego Sternberg
CEO, Nexton
Nexton

Built to assist, not to decide

Recommendations, not rejections.

No recordingNo biometric analysisNo data scraping

Live transcription, not recording. Candidate-provided data only. Messa flags, scores, and suggests. You make the call.

FAQ

Questions we get asked.

An LLM handles the pieces: summarize a CV, draft questions. But you're asking a model to improvise the method every time, and every interviewer runs it their own way. The notetaker just records whatever they did.

Messa is the system underneath all of it. A method built from how strong teams hire, tailored to your role, enforced on every interview so the bar holds whether or not anyone remembers to set it. Sidekick runs live beside the call, surfacing the right follow-up while it still matters. Every conversation resolves into one structured scorecard you can stand behind. The whole team works from the same context, and every hire sharpens the bar for the next one.

Messa works alongside your ATS, it does not replace it. Your ATS tracks where candidates are in the pipeline. Messa is the evaluation layer: it defines what to assess, builds the questions to focus on, guides the conversation as it happens, and captures structured evidence you can actually decide from, and stand behind.

Messa transcribes the conversation live so Sidekick can guide the interview and capture structured evidence as it happens. It does not store audio or video of the interview. That keeps the focus where it belongs, on what the candidate actually said and how they reasoned, not on a recording sitting in your systems. You get the evidence you need to evaluate, with far less sensitive data to secure, govern, and explain.

Any company that hires. Messa helps the company, the individual interviewer, and every stakeholder in the loop. The solo interviewer running several roles a week, with no time to research the person beforehand, who still wants to ask the right questions and write up real feedback after. The panel coordinator chasing interviewers who send feedback late, if at all, and are not sure what they are supposed to be assessing. And the company holding a consistent bar while it scales, across more roles and more interviewers than any one person can sit in on, including roles nobody on the team has done themselves. It works the moment you turn it on, and it gets sharper the more you put in.

In most companies, hiring lives in people's heads. Each interviewer asks what they think to ask and judges by their own bar. Messa gives you a proven method instead, built from what the experts in hiring actually do and dropped straight into your workflow: what to look for in each role, what to ask, how to score it, the same way every time. It lives in the software, so your team does not need to read it, configure it, or remember it. It just works.

Adaptive reads each skillset you need to evaluate, in the context of the role and your company, and designs the interview to probe for evidence of real excellence in that skill: behavioral for past performance, situational for judgment, case-based for problem solving, blending methods when a skillset demands more than one. You get an interview built around what you are actually evaluating, not a fixed template applied to every role. Your interviewers do not need to know any of this. Messa designs it and runs it.

Yes, and that is the point. Every role you run teaches Messa what good looks like on your team: the criteria you set, the bar you hold, the calls you make. That standard gets captured and reused instead of rebuilt from memory each time, so the tenth interview for a role is sharper than the first, and a new interviewer inherits the same bar as your most experienced one. Over time you are not just running interviews, you are compounding a standard for how your team evaluates talent. Your data stays yours and stays private. It works for your hiring, and no one else's.

See talent clearly.
Decide with confidence.

30 minutes. Real examples. Time for your questions.