Skip to content
juicebox-reference-architecture logo

Juicebox Reference Architecture

juicebox-reference-architecture

Implement Juicebox reference architecture.

SKILL.md

Full skill instructions

Juicebox Reference Architecture

Overview

Production architecture for AI-powered candidate analysis integrations with Juicebox. Designed for recruiting teams needing automated dataset ingestion from job descriptions, intelligent candidate scoring and ranking, result caching for repeated searches, and seamless export to ATS platforms like Greenhouse and Lever. Key design drivers: search result freshness, candidate deduplication across sources, outreach sequencing, and analysis pipeline throughput for high-volume hiring.

Architecture Diagram

Recruiter Dashboard ──→ Search Service ──→ Cache (Redis) ──→ Juicebox API
                             ↓                                /​search
                        Queue (Bull) ──→ Analysis Worker      /​profiles
                             ↓                                /​outreach
                        ATS Export Service ──→ Greenhouse/​Lever
                             ↓
                        Webhook Handler ←── Juicebox Events

Service Layer

class CandidateSearchService {
  constructor(private juicebox: JuiceboxClient, private cache: CacheLayer) {}

  async findAndRank(criteria: SearchCriteria): Promise<RankedCandidate[]> {
    const cacheKey = `search:${this.hashCriteria(criteria)}`;
    const cached = await this.cache.get(cacheKey);
    if (cached) return cached;
    const results = await this.juicebox.search(criteria);
    const ranked = results.profiles.map(p => ({ ...p, score: this.scoreCandidate(p, criteria) }))
      .sort((a, b) => b.score - a.score);
    await this.cache.set(cacheKey, ranked, CACHE_CONFIG.searchResults.ttl);
    return ranked;
  }

  async exportToATS(candidates: string[], jobId: string, ats: 'greenhouse' | 'lever'): Promise<ExportResult> {
    const deduped = await this.deduplicateAgainstATS(candidates, jobId, ats);
    return this.juicebox.export({ profiles: deduped, destination: ats, job_id: jobId });
  }
}

Caching Strategy

const CACHE_CONFIG = {
  searchResults: { ttl: 1800, prefix: 'search' },   // 30 min — candidate pools shift slowly
  profiles:      { ttl: 3600, prefix: 'profile' },   // 1 hr — profile data stable short-term
  analysisRuns:  { ttl: 7200, prefix: 'analysis' },   // 2 hr — analysis results are expensive to recompute
  atsState:      { ttl: 300,  prefix: 'ats' },        // 5 min — ATS pipeline freshness for dedup
  outreach:      { ttl: 60,   prefix: 'outreach' },   // 1 min — sequence status changes frequently
};
// New search invalidates matching cached results; ATS export clears ats cache for that job

Event Pipeline

class RecruitingPipeline {
  private queue = new Bull('juicebox-events', { redis: process.env.REDIS_URL });

  async onSearchComplete(searchId: string, results: RankedCandidate[]): Promise<void> {
    await this.queue.add('analyze', { searchId, candidateIds: results.map(r => r.id) },
      { attempts: 3, backoff: { type: 'exponential', delay: 2000 } });
  }

  async processOutreachEvent(event: OutreachEvent): Promise<void> {
    if (event.type === 'reply_received') await this.flagForRecruiterReview(event);
    if (event.type === 'bounced') await this.markInvalid(event.candidateId);
    await this.syncStatusToATS(event);
  }
}

Data Model

interface SearchCriteria   { role: string; skills: string[]; location?: string; experienceYears?: number; companySize?: string; }
interface RankedCandidate  { id: string; name: string; title: string; company: string; score: number; skills: string[]; profileUrl: string; }
interface OutreachSequence { id: string; candidateId: string; jobId: string; steps: OutreachStep[]; status: 'active' | 'replied' | 'bounced' | 'opted-out'; }
interface ExportResult     { exported: number; duplicatesSkipped: number; atsJobId: string; }

Scaling Considerations

  • Parallelize search requests across role categories — Juicebox API supports concurrent queries
  • Cache analysis results aggressively — AI scoring is the most expensive operation per candidate
  • Batch ATS exports by job requisition to minimize Greenhouse/​Lever API round-trips
  • Deduplicate candidates across searches before outreach to avoid double-contacting
  • Rate-limit outreach sequencing to maintain sender reputation and deliverability

Error Handling

ComponentFailure ModeRecovery
Candidate searchJuicebox API timeoutRetry with reduced result count, serve cached results if available
Analysis pipelineScoring model latency spikeQueue with timeout, return unscored results with flag
ATS exportGreenhouse rate limitBatch retry with exponential backoff, notify recruiter on persistent failure
Outreach sequenceEmail bounceMark candidate invalid, remove from active sequences, update ATS
Webhook handlerDuplicate event deliveryIdempotency key on event ID + candidate ID

Resources

Next Steps

See juicebox-deploy-integration.

More DevOps & CI/CD skills

Project scaffolding, deployment configuration, and CI/CD setup for Google ADK agents.

6K 472.6K
View

Set up tracing, logging, and monitoring for deployed ADK agents across Cloud Trace, BigQuery, and third-party platforms.

6K 472.6K
View

Enterprise Azure infrastructure architect generating Bicep or Terraform from workload descriptions.

1.5K 454.3K
View
azure-kubernetes logo
DevOps & CI/CD

azure-kubernetes

Plan and configure production-ready Azure Kubernetes Service clusters with Day-0 and Day-1 best practices.

1.5K 447.1K
View

Raw mechanical interfaces fusing Swiss typographic print with military terminal aesthetics. Rigid grids, extreme type scale contrast, utilitarian color, analog degradation effects. For data-heavy dashboards, portfolios, or editorial sites that need to feel like declassified blueprints.

92.7K 354.9K
View
just-scrape logo
DevOps & CI/CD

just-scrape

Web search, scraping, extraction, crawling, and monitoring via ScrapeGraph AI CLI.

69 245K
View

Skill for working with Firebase Hosting (Classic). Use this when you want to deploy static web apps, Single Page Apps (SPAs), or simple microservices. Do NOT use for Firebase App Hosting.

462 159.7K
View

Deploy and manage web apps with Firebase App Hosting. Use this skill when deploying Next.js/Angular apps with backends.

462 159.1K
View
deploy-to-vercel logo
DevOps & CI/CD

deploy-to-vercel

Deploy applications and websites to Vercel. Use when the user requests deployment actions like "deploy my app", "deploy and give me the link", "push this live", or "create a preview deployment".

31.9K 146.6K
View
programmatic-seo logo
DevOps & CI/CD

programmatic-seo

Build SEO-optimized pages at scale using templates, data, and proven playbook patterns.

53.3K 140.1K
View

Design and build isolated, reusable Convex backend components with clear boundaries and app-facing wrappers.

63 123.5K
View

Deploy and manage projects on Vercel using token-based authentication. Use when working with Vercel CLI using access tokens rather than interactive login — e.g. "deploy to vercel", "set up vercel", "add environment variables to vercel".

31.9K 116.1K
View

Coding & apps AI tools

Opus Clip logo
Coding & apps

Opus Clip

Opus.ai: Revolutionize Your Web Experience

Free
View
Imagica logo
Coding & apps

Imagica

Build a no-code AI app in minutes.

Freemium
View
E
Coding & apps

Emergent.sh

An IDE for code migration from legacy to modern frameworks through coding agents.

Freemium
View
Wonder Dynamics logo
Coding & apps

Wonder Dynamics

Automate CGI animation in live-action scenes

Paid
View
M
Coding & apps

Mixo

Launch a website in seconds with AI.

Paid
View
AI Code Convert logo
Coding & apps

AI Code Convert

Streamline Your Coding Experience with AI Code Helper

Free
View