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Platform Reliability (Horizon AI)

STN Incorporated

Role overview

Qualifications

  • Production experience making distributed systems reliable
  • Comfort in Python and containerized environments
  • Experience with event streaming and understanding failure modes
  • Observability depth: metrics, distributed tracing, and alerting

Responsibilities

  • Build the caching layer to prevent external system calls
  • Implement event streaming to reduce synchronous dependencies
  • Harden agent dispatch with health checks, circuit breakers, and retries
  • Build observability metrics, tracing, and actionable alerting

Key facts

Hard skills

About the company

STN Incorporated logo

STN Incorporated

IT Services & IT Consulting

At STN, we don’t just deliver technology, we build the foundation that modern organizations run on. From enterprise IT to AI infrastructure, we design, operate, and support systems that are reliable, secure, and built for performance. But what sets us apart isn’t just our stack it’s how we show up. We don’t believe in one-size-fits-all. We don’t drop in hardware and disappear. We work side by side with our customers to understand what they actually need and build solutions that fit, flex, and scale as they grow.Whether you're running business-critical systems, deploying AI models, or training large-scale workloads on NVIDIA GPUs, we’re here to make sure your infrastructure isn’t just running, it’s working for you. Our team brings deep technical expertise, hands-on support, and a people-first mindset to everything we do. Because we believe technology should unlock potential, not create more problems. STN exists to help teams thrive in complex environments with custom engineering, real partnership, and a clear plan forward.

Company details

IndustryIT Services & IT Consulting
Company size11 - 50

Links

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Job description

Platform Reliability

Level: Staff (MTS 4) · Reports to: Chief AI Officer, later the Senior Engineering Manager

The role. Make our own platform dependable and scalable, working with the Principal Engineer. This is reliability engineering for Horizon AI’s software rather than for the GPU fleet, though the two meet when our agents are the ones being trusted with fleet actions.

You will

  • Build the caching layer that stops every agent tool call from hitting external systems directly

  • Implement event streaming so services stop depending on synchronous HTTP chains

  • Harden agent dispatch: health checks, circuit breakers, retry semantics, and observability that distinguishes failure from degradation

  • Build observability of our own platform: service-level metrics, tracing across services, and alerting we act on

  • Contribute to the orchestration migration and to infrastructure-as-code

  • Improve deployment practice: canary, traffic shifting, and real rollback

You have

  • Production experience making distributed systems reliable: caching, queuing, circuit breaking, backpressure, timeouts, idempotency

  • Comfort in Python and containerized environments, with real exposure to Kubernetes or equivalent orchestration

  • Experience with event streaming and with the failure modes each option brings - Observability depth: metrics, distributed tracing, and the judgment to alert on symptoms rather than causes

  • A record of shipping reliability improvements with measurable before and after

Nice to have: durable workflow orchestration, blue/green and canary deployment at scale, performance profiling of Python services

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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