Agent Felet – Multi Agent Systems, Horizon AI

Job not on LinkedIn

🕒 October 21

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Artificial Intelligence

👻 Ghost score 17%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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STN Incorporated

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2016

🏢 Enterprise

🔒 Cybersecurity

🔧 Hardware

Enterprise • Cybersecurity • Hardware

STN Incorporated is an enterprise-grade managed IT and cloud infrastructure provider that delivers secure, audit-ready infrastructure for business-critical systems and demanding AI workloads. STN operates a managed operating model offering private CPU clouds, GPU One AI infrastructure, secure networking and storage, and 24/7 human support with high uptime SLAs. Their services include managed infrastructure and cloud operations, cybersecurity operations and incident response, compliance and risk management (SOC 2 Type II, HIPAA-ready), backup and recovery, and enterprise technology procurement and lifecycle management. STN serves enterprises, high-growth SaaS companies, AI builders and model developers, robotics/physical AI firms, and regulated industries such as healthcare.

📋 Description

• Build the evaluation harness for agent behaviour, including scenario suites from real incidents, CI regression gating, and metrics that detect confidently wrong agents • Define the autonomy SLO with the Chief Architect and own evidence for moving decisions from recommendation to action • Own agent architecture, including orchestration, tool dispatch, task decomposition, escalation, and read/write governance boundaries • Improve agent reasoning explanations so recommendations can be acted upon • Encode operational runbooks into agent-executable reasoning

🎯 Requirements

• Built and shipped LLM-based agentic systems in production, including malformed tool output, loops, stuck states, and context exhaustion • Strong and specific opinions about evaluation • Experience with tool and function calling at scale • Experience with LLM tracing and online evaluation • Strong systems engineering fundamentals in Python • Experience with multi-agent orchestration, handoff, and context management • Nice to have: operational or SRE background • Nice to have: human-in-the-loop system design • Nice to have: retrieval over operational data • Nice to have: experience defining what an autonomous system is allowed to do

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