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ibarrajotoday at 12:11 AM0 repliesview on HN

  Location: Seattle, WA
  Remote: Yes
  Willing to relocate: Yes (SF, NYC for the right team)
  Technologies: Go, Python, Kotlin, TypeScript, Rust | Cadence/Temporal, Kafka, gRPC, Postgres, Redis, Kubernetes | AWS, GCP, Cloudflare | LLM agents, MCP, Playwright/CDP, RAG
  Résumé: https://elninja.com/resume
  LinkedIn: https://www.linkedin.com/in/elninja
  GitHub: https://github.com/ibarrajo
  Email: alex [at] elninja.com
Senior backend / platform IC, 10+ years on distributed systems at Uber, DoorDash, Jobscan. Looking for a hands-on senior IC role — infrastructure, developer platforms, or applied AI systems.

At Uber, Developer Advocate for Cadence — the open-source workflow engine running 12B+ workflows/month internally. Onboarded 50+ teams, executed multi-region failovers on domains processing billions of daily ops, rebuilt cadenceworkflow.io, and shipped non-determinism detection via shadow replay. Before Uber: refund rules engine for McDonald's/Chipotle at DoorDash (500K refunds/month), and Interim Head of Engineering at Jobscan (97% → 99.99% uptime on AWS migration, $475K/yr recovered via payment A/B testing).

Currently shipping (June 2025 → now):

- Pursuit (co-founder, AI Scalathon Seattle 2026): agent-to-agent recruiting — a 3-min structured candidate/employer interview producing ranked multi-dimensional match scores. Ran live: 51 reports + 120 real matches against Microsoft, JPMorgan, Uber, CoreWeave, Adobe, Block, Boeing, Lululemon, SpaceX.

- Meridian: 29k-line TypeScript autonomous goal-graph executor (Postgres + MCP) that decomposes high-level charters into plan nodes and runs LLM-backed agents on a real-time dashboard.

- ApplyPilot (OSS, github.com/ibarrajo/ApplyPilot): multi-provider LLM orchestration with cost-aware routing across Gemini/OpenAI/Anthropic; Claude Code + Playwright integration across 40+ ATS workflows.

- OpenAI Parameter Golf: 14+ PRs opened to the 16MB / 10-min / 8xH100 LLM-training challenge. Hands-on with Int5/6 GPTQ, test-time training with score-first backprop, Triton kernels, Hessian-based calibration.

Looking for a team where shipping daily is the norm.