nextcraft/packages/mock-data/candidates.ts

import type { Candidate } from '@nextcraft/types';

export const candidates: Candidate[] = [
  {
    id: 'cand-001',
    name: 'Maya Okonkwo',
    avatar: 'https://i.pravatar.cc/150?img=1',
    headline: 'AI Orchestration Engineer · Multi-agent systems, RAG, evaluation',
    competencyStackId: 'stack-orchestration',
    microcredentials: 11,
    artifactCount: 12,
    defenseScore: 92,
    matchScore: 96,
    bio: 'Shipped two production agent systems handling 4M+ queries/week. Evidence portfolio includes a multi-agent research assistant with full eval harness.',
  },
  {
    id: 'cand-002',
    name: 'Devon Park',
    avatar: 'https://i.pravatar.cc/150?img=2',
    headline: 'AI Safety Researcher · Alignment, red teaming, interpretability',
    competencyStackId: 'stack-safety',
    microcredentials: 10,
    artifactCount: 9,
    defenseScore: 90,
    matchScore: 91,
    bio: 'Published two workshop papers on jailbreak robustness. Runs an automated red-team suite with 1,200+ probes across three model families.',
  },
  {
    id: 'cand-003',
    name: 'Priya Iyer',
    avatar: 'https://i.pravatar.cc/150?img=3',
    headline: 'Human-AI Product Designer · Agentic UX, trust calibration',
    competencyStackId: 'stack-designer',
    microcredentials: 9,
    artifactCount: 11,
    defenseScore: 88,
    matchScore: 89,
    bio: 'Designed the transparency system for an assistant with 2M MAU. Portfolio includes a full human-in-the-loop review pattern library.',
  },
  {
    id: 'cand-004',
    name: 'Tomás Vega',
    avatar: 'https://i.pravatar.cc/150?img=4',
    headline: 'LLM Application Developer · RAG, function calling, streaming',
    competencyStackId: 'stack-orchestration',
    microcredentials: 12,
    artifactCount: 10,
    defenseScore: 87,
    matchScore: 93,
    bio: 'Built a document-grounded Q&A product from zero to 50K daily actives. Specializes in retrieval quality and output validation.',
  },
  {
    id: 'cand-005',
    name: 'Hana Lindqvist',
    avatar: 'https://i.pravatar.cc/150?img=5',
    headline: 'Computational Biologist · Drug discovery, ML pipelines',
    competencyStackId: 'stack-science',
    microcredentials: 13,
    artifactCount: 8,
    defenseScore: 91,
    matchScore: 88,
    bio: 'Active-learning pipeline nominated for a phenotype-prediction benchmark. Reproducible workflows with Snakemake and containerized HPC jobs.',
  },
  {
    id: 'cand-006',
    name: 'Marcus Bell',
    avatar: 'https://i.pravatar.cc/150?img=6',
    headline: 'Robotics Operations Specialist · Vision systems, field AI',
    competencyStackId: 'stack-operator',
    microcredentials: 8,
    artifactCount: 7,
    defenseScore: 84,
    matchScore: 78,
    bio: 'Five years on a warehouse robotics fleet. Built an anomaly-triage dashboard that cut false-positive escalations by 40%.',
  },
  {
    id: 'cand-007',
    name: 'Sofia Marchetti',
    avatar: 'https://i.pravatar.cc/150?img=7',
    headline: 'AI Governance Lead · NIST AI RMF, audit, model cards',
    competencyStackId: 'stack-safety',
    microcredentials: 11,
    artifactCount: 6,
    defenseScore: 89,
    matchScore: 85,
    bio: 'Stood up AI governance at a 5,000-person org. Authored 14 model cards and a risk register covering 30+ deployed systems.',
  },
  {
    id: 'cand-008',
    name: 'Liam Chen',
    avatar: 'https://i.pravatar.cc/150?img=8',
    headline: 'Agent Reliability Engineer · Observability, tracing, SRE',
    competencyStackId: 'stack-orchestration',
    microcredentials: 10,
    artifactCount: 9,
    defenseScore: 86,
    matchScore: 90,
    bio: 'Owns tracing for an agent platform serving 200+ internal teams. Built a token-cost alerting system that saved $1.2M/year.',
  },
  {
    id: 'cand-009',
    name: 'Amara Diallo',
    avatar: 'https://i.pravatar.cc/150?img=9',
    headline: 'Climate ML Scientist · Forecasting, data assimilation, PINNs',
    competencyStackId: 'stack-science',
    microcredentials: 12,
    artifactCount: 8,
    defenseScore: 90,
    matchScore: 84,
    bio: 'Downscaled GCM output for a regional energy grid operator. Physics-informed model improved 72-hour wind forecasts by 18%.',
  },
  {
    id: 'cand-010',
    name: 'Ethan Whitfield',
    avatar: 'https://i.pravatar.cc/150?img=10',
    headline: 'AI Product Manager · Roadmapping, AI UX, metrics',
    competencyStackId: 'stack-designer',
    microcredentials: 9,
    artifactCount: 5,
    defenseScore: 82,
    matchScore: 80,
    bio: 'Shipped an agentic coding assistant to 30K developers. Defined the success metrics and evaluation framework for the v1 launch.',
  },
  {
    id: 'cand-011',
    name: 'Yuki Tanaka',
    avatar: 'https://i.pravatar.cc/150?img=11',
    headline: 'Evaluation Engineer · LLM-as-judge, regression suites',
    competencyStackId: 'stack-orchestration',
    microcredentials: 10,
    artifactCount: 8,
    defenseScore: 85,
    matchScore: 86,
    bio: 'Built an eval platform that runs 50K+ judged samples per model release. Calibrated LLM-as-judge against human panels to 0.87 agreement.',
  },
  {
    id: 'cand-012',
    name: 'Olu Adeyemi',
    avatar: 'https://i.pravatar.cc/150?img=12',
    headline: 'Conversation Designer · Dialogue flows, persona systems',
    competencyStackId: 'stack-designer',
    microcredentials: 8,
    artifactCount: 7,
    defenseScore: 83,
    matchScore: 77,
    bio: 'Designed repair flows that reduced user frustration escalations by 35%. Authored a persona consistency framework now used company-wide.',
  },
  {
    id: 'cand-013',
    name: 'Nadia Petrova',
    avatar: 'https://i.pravatar.cc/150?img=13',
    headline: 'Materials ML Engineer · Property prediction, active learning',
    competencyStackId: 'stack-science',
    microcredentials: 11,
    artifactCount: 9,
    defenseScore: 88,
    matchScore: 82,
    bio: 'Active-learning loop identified three experimentally-validated novel alloys. Maintains an open-source DFT active-learning toolkit.',
  },
  {
    id: 'cand-014',
    name: 'Rafael Costa',
    avatar: 'https://i.pravatar.cc/150?img=14',
    headline: 'Edge AI Engineer · Quantization, TensorRT, field deployment',
    competencyStackId: 'stack-operator',
    microcredentials: 9,
    artifactCount: 8,
    defenseScore: 84,
    matchScore: 83,
    bio: 'Quantized a vision model from 240MB to 11MB with <1% accuracy loss. Deployed to 3,000+ edge devices with OTA model updates.',
  },
  {
    id: 'cand-015',
    name: 'Ingrid Solberg',
    avatar: 'https://i.pravatar.cc/150?img=15',
    headline: 'AI Red Team Lead · Adversarial testing, disclosure, policy',
    competencyStackId: 'stack-safety',
    microcredentials: 10,
    artifactCount: 7,
    defenseScore: 87,
    matchScore: 88,
    bio: 'Led red-teaming for two frontier model releases. Coordinated three coordinated disclosures with partner labs.',
  },
];