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Elloe Ai

Principal Engineer – Distributed Systems (GPU Edge + Inference)

  • Remote (United States)
  • remote
  • Full time
  • Principal

Posted

Free to apply. You’ll finish on the employer’s own site.

Full-time | Remote | Infrastructure | Reports to CTO
About ElloeElloe is the trust layer for AI.We sit between the world’s most powerful language models and the institutions that can't afford to get it wrong — hospitals, banks, regulators. We trace and block failures in real time. That’s not marketing — we’re deployed at the European Commission, with NIH clinical trials, and inside a Top-5 EU bank catching GDPR violations live.
This is the enforcement layer GenAI has been missing. We're not visualizing problems — we're fixing them.
About the RoleYou’ll lead our GPU-edge inference systems. From chaos-resilient deployment to SHAP-driven compliance metrics, you’ll own global infra that makes AI safe and performant.
What You’ll Own1. Global Edge Routing
  •   Design zone-routing that ensures <50ms SLA in 10+ regions
  •   Build fallback orchestration to handle compliance-aware rollbacks
2. GPU Infra Ops
  •   Maximize utilization across 100K+ GPUs via mesh & load prediction
  •   Integrate compliance overlays with VaultChain and SHAP triggers
3. Reliability Telemetry
  •   Ship `/vault/audit`, `/inference/predict`, `/compliance/log` endpoints
  •   Trace every edge request across governance and model layers

Who You Are
  • Senior systems engineer with GPU fleet experience (KubeRay, Istio, Envoy)
  • Operated real-time AI infra with 10M+ QPS loads
  • Comfortable with compliance observability and infra governance

Why This MattersOur competitive edge isn’t just AI — it’s defensible enforcement. This role turns that into product.
You’ll Leave This Role With
  • Referenceable contributions to enforcement infra that’s live in EU and US institutions
  • First-hand product work across legal, engineering, and GTM teams
  • Influence over how regulatory primitives become systems people trust

Logistics & Application
  • Start Date: Flexible (Q3–Q4 ideal)
  • Location: Remote-first; timezone overlap with NY or EU preferred
  • Compensation: Top of market salary + equity
  • To Apply: Send your resume and a sentence on the hardest infra problem you'd want to own at scale.

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Principal Engineer – Distributed Systems (GPU Edge + Inference)Elloe Ai
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