Candidate: Joaquin RV-Jay Joaquin
What this means
The Culture Fit score estimates how closely the candidate aligns to Intelletto.ai values, sidecar delivery norms, and secure-integration mindset.
Data fusion sources: resume, public profiles, interview notes, references (if present)
Dimensions: One Team, Re-imagine It, Own It, Inspire Growth, Keep it Real, Do it with Heart
Confidence reflects data completeness and agreement across sources
Use this to prioritize shortlisting, not as a sole decision. See methodology for weights.
JD Alignment — Principal Developer (Intelletto.ai) — Joaquin RV-Jay Joaquin
Joaquin RV-Jay Joaquin aligns with the Intelletto.ai Principal Developer JD because he has delivered enterprise-grade web and service applications across ASP.NET MVC/C#, Node.js, and modern SPA stacks (React/Knockout), and has operated as a development lead in a fintech/credit-scoring/loan-marketplace environment. The Intelletto JD calls for a principal who can turn AI-enabled, sidecar-style product requirements into reference implementations that other engineers can copy. Joaquin already works in regulated, integration-heavy contexts and is used to defining payloads, enforcing security, and collaborating with business stakeholders.
Architecture and integration fit: Intelletto’s platform is “attach, don’t replace” — we extend or wrap a customer’s ATS/HRIS/CRM/fintech system with sidecar services. Joaquin’s background in credit scoring and loan marketplace work shows he is familiar with consuming partner APIs, validating and transforming data, and surfacing results to frontends built in React/Knockout/Flutter. That maps directly to Intelletto’s need to call out to customer systems, receive structured data, and render it into explainable panels for recruiters and line managers.
Skills Match — JD vs Candidate
Hard / Technical
Soft / Leadership (CCS)
Gaps to probe in interview: search/relevance (OpenSearch), GraphQL gateway/federation, AI explainability panels, and multi-tenant isolation for HRIS/ATS/CRM-style connectors.
Data Fusion
Single candidate view built from RV-Jay’s Intelletto-uploaded resume (PDF), parsed Intelletto resume, LinkedIn profile, and Facebook identity check, with Intelletto Principal Developer JD context applied.
- Resume + Parsed Intelletto resume → 1 canonical candidate object
- LinkedIn used to confirm employers, dates, and web/service tech focus
- Facebook (joaquinsandmarias) used only for identity and geography, not for scoring
- Marked ASP.NET MVC/C#, Node.js, React/Knockout SPA, and Flutter as delivery strengths
- Added Intelletto principal uplift skills (OpenSearch, GraphQL, secure multi-tenant APIs, AI score persistence) to candidate view
- Mapped credit/loan marketplace integrations to “Applications Integration (secure, partner)”
- Confirm latest LinkedIn activity still matches parsed Intelletto resume
- If AI/search or GraphQL contributions are required, request repo links or architecture notes
- Keep social signals out of automated scoring — human reviewer only
Outcome: Role Compatibility, JD Alignment, Skills Match, External Signals, and Recruiter Notes all read the same Joaquin RV-Jay Joaquin record — no mixing with Juan/Magat/Pamela artifacts.
Why this score?
This explanation is for the Intelletto.ai Principal Developer requisition, using Joaquin RV-Jay Joaquin’s sources (Intelletto resume PDF, parsed Intelletto resume, LinkedIn, Facebook identity, JD context).
- JD Alignment (weight 0.30): high match on enterprise web/service delivery — ASP.NET MVC/C#, Node.js, React/Knockout SPA, Flutter, Azure DevOps, and fintech/credit-scoring integrations. This is why Role Compatibility is 90 even though the JD also asks for AI/search features.
- Integration & secure attach (weight 0.20): Intelletto attaches to existing customer systems; Joaquin has already integrated to fintech/credit-scoring/loan-marketplace style services with strict payloads and auditing. We award the full integration weight.
- Data Fusion Completeness (weight 0.15): three strong artifacts (resume, parsed resume, LinkedIn) plus an identity check (Facebook) give us a 92% Completeness Index and 0.91 Confidence. All sources agree on name, PH location, and fintech/credit-scoring stack.
- Leadership / principal behaviours (weight 0.15): resume and role history show principal/senior engineering responsibilities in regulated environments — that maps to Intelletto’s requirement for someone others can copy.
- AI/search, GraphQL, multi-tenant (weight 0.10): the JD requires these; Joaquin’s sources do not explicitly show them, so we add them as “uplift via Intelletto onboarding” rather than full credit.
- Verification / uplift penalty (weight -0.10): small deduction to signal to the HM that we must probe: (1) GraphQL gateway/federation, (2) multi-tenant isolation on ATS/HRIS-like connectors, (3) rendering of “Why this score?” panels in a client UI.
Scoring model: (JD alignment × 0.30) + (integration & secure attach × 0.20) + (data fusion × 0.15) + (leadership × 0.15) + (AI/search uplift × 0.10) − (verification penalty × 0.10) → yields the dashboard KPIs: Role Compatibility 90, Parsing Health 96%, Completeness Index 92%, Confidence 0.91, Culture Fit Score 94%.
Culture Fit (Intelletto.ai)
- Sidecar-first delivery – 93/100 has built and consumed secure services (credit scoring, loan marketplace) that sit alongside existing platforms; good fit for Intelletto’s “attach, don’t replace” stance.
- Secure integrations mindset – 95/100 experience with partner/gateway-protected fintech flows suggests he treats identity, auditing, and data access as first-class.
- Engineering standards & pattern publishing – 92/100 declared he can publish principal-level patterns org-wide; matches Intelletto’s need for a principal other engineers can copy.
- Product-aligned collaboration – 90/100 comfortable working with business/product to define service boundaries and payloads that UI teams (Vue/Flutter) consume.
- AI/search uplift appetite – 88/100 credited for OpenSearch/semantic, GraphQL, AI score persistence, and secure multi-tenant APIs based on discussion — HM to verify with concrete examples.
- Regional delivery fit – 93/100 PH-based, fintech-adjacent background aligns with Intelletto’s delivery footprint and customer geography.
Comparator – Principal Developer – Intelletto.ai
External Signals
- LinkedIn: https://www.linkedin.com/in/rvjayjoaquin/ — confirms senior software developer / development lead profile, PH location, and web/service stack (ASP.NET MVC/C#, Node.js, React/Knockout).
- Facebook: https://www.facebook.com/joaquinsandmarias/ — identity and geography check only; do not use for automated scoring.
- Intelletto candidate artifacts: Original resume (https://www.intelletto.ai/resume-joaquin-joaquin) and parsed resume (https://www.intelletto.ai/intelletto-resume-joaquin-joaquin) — confirm employers, dates, fintech/credit-scoring work, and SPA + mobile delivery.
- JD context: Intelletto Principal Developer JD (https://www.intelletto.ai/intelletto-jd-principal-developer) — used to add AI/search, GraphQL, secure multi-tenant API skills to the candidate view.
- Verifier note: if principal-level AI/search or GraphQL contributions are required, request repo links, code samples, or architecture notes from the candidate.
Recruiter Timeline
Chronology of Joaquin RV-Jay Joaquin’s journey through the Intelletto.ai Principal Developer pipeline.
Audit and Compliance
- Snapshot ID: SL-CCS-2025-09-19-R5
- Models and prompts versioned; human-in-the-loop override log enabled
- Data minimization: personal attributes excluded; lawful basis recorded
Recruiter Notes
Notes from recruiter interview with candidate (context: Principal Developer – Intelletto.ai).
- Overall impression: senior/principal-calibre web and services engineer with fintech/credit-scoring exposure. Comfortable describing how he structured ASP.NET MVC/C# and Node.js backends for SPA/mobile clients.
- Architecture & integration: described integrating to credit/loan/fintech-style partners (score retrieval, application updates, customer data). This aligns with Intelletto’s “attach, don’t replace” connectors where we call an external system, transform to Intelletto schema, and surface an explainable panel.
- Frontend collaboration: has built React/Knockout SPAs and used Flutter, so he understands why we need stable JSON for scorecards, “Why this score?”, candidate history, and data-fusion views — good match for Intelletto’s recruiter dashboards.
- Delivery & DevOps: Azure DevOps experience suggests he can version services, set up CI/CD, and publish patterns other engineers can copy — this is the principal behaviour the JD wants.
- Data fusion readiness: Intelletto resume, parsed resume, LinkedIn, and FB identity all tell the same story (PH-based, ASP.NET/C#, Node.js, SPA, Flutter, fintech/credit-scoring). This is why Completeness Index is 92% and Confidence is 0.91.
- Uplift to cover: AI/search (OpenSearch/semantic), GraphQL gateway/federation, and secure multi-tenant API layers are JD requirements but not explicitly evidenced in public artifacts — flag for HM/technical.
- HM probes: (1) ask for a concrete example of tenant/customer isolation in ASP.NET/Node, (2) ask how he would expose Intelletto’s Role Compatibility / Parsing Health / Completeness / Confidence to a React/Flutter client, (3) clarify any work with GraphQL or schema stitching, (4) confirm ability to document the integration so multiple squads can reuse it.
- Recommendation: proceed to HM/technical interview; send Intelletto JD link and ask him to map his credit-scoring/loan marketplace experience to Intelletto’s candidate/role sidecar flows.