MetaOne Designs (M1D) - Architecture Zero, TheStatic.tv, JobTrue · Remote

• Architected Architecture Zero, a private white-label AI platform running four live production instances from one core codebase - hybrid RAG (vector + custom Okapi BM25 + cross-encoder reranker), department-scoped knowledge bases with role-based access, multi-provider LLM routing (Claude / GPT / local Ollama) with failover, and local inference (7B to 30B-class models on RTX 5090/3090 hardware).
• Drove retrieval recall from 40% to a measured 100% (50/50 retrieval-scored, stamped in-app), then grew the harness to a 98-question cross-family-judged instrument (answers and grades come from structurally different labs) - current floors: 98.6% recall, 91.0 tuned answers vs an outside-authored locked holdout with the 11.3-point overfit gap published, honesty cohort 13/13 - via cross-encoder reranking, markdown-section chunking, a full-corpus BM25 leg, and content-addressed delta ingestion that cut re-index costs from ~470 chunks to ~10 per update.
• Built Eco Mode, a federated retrieval mesh: instances query each other's knowledge in parallel with per-caller scoped keys and fail-closed access boundaries - a public bot can never reach private departments; verified by adversarial testing as the least-privileged caller.
• Hardened the fleet with automated CI security gating (gitleaks, pip-audit, bandit, trivy), OWASP Web + LLM Top 10 mapping, per-IP rate limiting behind a proxy-aware real-client-IP boundary, and self-audited postmortems - found and closed a real broken-access-control bug, then published the case study.
• Shipped TheStatic.tv solo: a production Web3 streaming platform - 160+ authenticated API endpoints, GCP Livestream RTMP/HLS pipeline, a cron-driven billing engine with Redis distributed locks and viewer-scaled burn rates, and an ERC-721 contract on Ethereum mainnet.
• Shipped JobTrue (jobtrue.ai) solo: an AI job-search SaaS with Stripe billing, LLM fit-scoring with a server-side grounding layer that drops hallucinated resume items before storage, and per-user rate limiting - this resume is served from it.
• Operate everything built - hosting, CI/CD, monitoring, security review, documentation - plus nightly encrypted backups to immutable object storage (Cloudflare R2 bucket-lock + Google Drive) and an automated daily restore drill that boots each backup in a throwaway container: 9/9 checks, alarmed end-to-end via a fail-closed status probe.
• Calibrated the LLM-as-judge eval instrument against four independent references - a 32-case planted-error suite (32/32 caught), a human-adjudicated baseline (Cohen's kappa 0.61), a cross-lab re-grade (99.0% agreement, kappa 0.942), and an independently-authored harness (98.2% boundary agreement) - then audited my own locked exam, retired it for authorship bias, re-authored it via a third lab, and published the wider honest gap.
• Designed refuse-vs-fabricate honesty evals - cohorts demanding artifacts the corpus does not hold, scored by a purpose-built judge rubric with planted calibration - measured 12/12 and 13/13; separately drove an adversarial tier-isolation cohort from 3/11 to 11/11 by locating an access leak diffused across the corpus, with owner recall held at 100%.
• Rolled the measured trust layer across all four production instances, validating each port with like-for-like A/Bs on that instance's own cohort: +12 correctness on one peer, +18.4 recall with rank-1 hits doubled on another, and multi-turn follow-up retrieval driven 1/9 to 8/9 by a measure-gated resolver port.
• Eliminated hand-set status from the platform's trust dashboards: every displayed number derives from stored eval runs or live config at request time; 42 reliability-layer claims each self-verify against activation-keyed code proofs on every deploy; the tuned-vs-holdout overfit gap is published as a first-class metric even when negative.
• Root-caused silent production failures behind green health checks: an HNSW vector-index corruption (search dead while reads passed - shipped a knn tripwire plus per-run corpus fingerprinting) and two distinct vector-store data-loss mechanisms (flush-boundary loss on unclean stops; a file-watcher mass-purge during git deploys) - fixed and verified with back-to-back zero-loss deploy cycles.

Conduent supporting Boeing · Everett, WA

• Maintain operational availability of testing workstations for aerospace manufacturing candidate assessments with a zero-downtime requirement.
• Serve as primary on-site contact for all technical issues; resolve hardware, peripheral, and connectivity problems and escalate to remote engineering when needed.
• Enforce strict site security and technical protocols as the on-the-ground liaison for off-site infrastructure managers.

Decentraland Foundation · Remote

• Provided technical support for creators and developers building on the Decentraland metaverse platform across Intercom, Discord, and Slack.
• Troubleshot SDK issues, scene deployment problems, wearables, and platform bugs; documented reproductions and coordinated with engineering teams for resolution.
• Leveraged 4+ years of hands-on Decentraland development experience to give expert-level guidance to the creator community.

Symetrix, Inc. · Mountlake Terrace, WA

• Drove live call answer rate from under 25% to over 80% by rebuilding NetSuite case-routing workflows and KPI tracking as primary NetSuite administrator.
• Cut Return Authorization turnaround from several weeks to 1-2 weeks by redesigning the process mid-2024.
• Hired as Tier 2 support; promoted to Team Lead in June 2023. Recognized publicly by the VP of Sales & Marketing for the call and case routing overhaul.
• Completed a NetSuite-ZOHO integration proof of concept; 2024 review: Exceeds Expectations across quality, initiative, technical skills, and dependability.

SAP Concur · Bellevue, WA

• Maintained 98% customer satisfaction across a high-volume enterprise Tier 3 queue for SAP Concur expense and travel products.
• Served as Comms lead on the Incident Response Team for P1/P2 issues - owned customer and stakeholder communication under SLA pressure while Tech and Lead drove resolution.
• Queried client data with SQL to diagnose enterprise issues during Tier 3 troubleshooting; mentored team members and built performance dashboards.