AI/LLM Safety Engineer

Job not on LinkedIn

🕒 October 16

🌪️ Kansas – Remote

🌪️ Kansas – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Artificial Intelligence

👻 Ghost score 12%

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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📋 Description

• Own the safety of models and agents in production, focusing on AI Safety, Trust & Safety, and Responsible AI • Design and maintain adversarial prompt sets, scenario-based test suites, and regression suites • Validate every model and agent update before release • Lead red-teaming exercises covering jailbreaks, prompt injection, tool misuse, and data exfiltration • Document findings and drive issues through remediation and closure • Build and iterate on input/output filtering, tool-boundary constraints, action validation, sensitive-data redaction, and policy prompting • Integrate safety checks into CI/CD and runtime systems • Threat-model agentic scenarios involving tool-call boundaries, sandbox isolation, and least-privilege access • Prevent data exfiltration and irreversible actions through chained tool calls • Review reinforcement-learning environments and trajectory data with environment and agent engineering teams • Instrument AI features with structured logging, tracing, and metrics • Prepare test reports, evaluation summaries, and mitigation validation for governance reviews • Collaborate with Product, UX, Research, and Data teams on safety interactions and evaluation goals

🎯 Requirements

• Bachelor's or Master's degree in Computer Science, Software Engineering, Cybersecurity, or a related technical field—or equivalent practical experience • 4+ years building production software, with direct experience working on or securing ML/LLM systems • Strong software engineering skills and ability to write production-grade code, primarily Python • Solid understanding of LLMs and ML, including model operation, prompt engineering, fine-tuning safety implications, and RAG risks • Security mindset with demonstrated threat-modeling ability • Familiarity with access control, data retention, and incident response fundamentals • Familiarity with prompt injection, jailbreaks, data poisoning, supply-chain risk, and OWASP LLM Top 10 • Hands-on experience with safety evaluation or red teaming, including explaining a real finding and its remediation • Preferred: experience with garak, PyRIT, promptfoo, Giskard, and NeMo Guardrails • Preferred: publications, open-source contributions, or responsible disclosures in AI safety or security • Preferred: familiarity with NIST AI RMF, ISO/IEC 42001, and EU AI Act • Preferred: engineering experience with agents, RL environments, and/or tool use • Preferred: experience with MITRE ATLAS and STRIDE/PASTA

🏖️ Benefits

• Opportunities to learn, develop, and expand capabilities • Meaningful career growth opportunities • Opportunities to pursue leadership opportunities and expand career path • Support for professional growth and innovation • Opportunity to make a meaningful impact • Flexible, empowered decision-making and ownership of initiatives

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