AI/LLM Safety Engineer

Job not on LinkedIn

🕒 June 26

🌪️ Kansas – Remote

🌪️ Kansas – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Artificial Intelligence

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Propio Aruba Realty

WebsiteLinkedInAll Job Openings

1 - 10 employees

💼 Consulting

⚖️ Legal

🏠 Real Estate

Consulting • Legal • Real Estate

Propio Aruba Realty is a real estate company based in Aruba that specializes in buying, selling, and renting residential and commercial properties. Offering services for property seekers looking for ideal locations and prices, Propio Aruba Realty serves both local and international clients. Their offerings include residential properties such as houses and apartments, commercial buildings, land, and business locations. The company provides detailed listings and assistance to guide clients to the perfect real estate solution.

📋 Description

• Design and maintain a safety evaluation framework—adversarial prompt sets, scenario-based test suites, and regression suites—so that every model and agent update is validated before it ships. • Lead structured red-teaming exercises covering jailbreaks, prompt injection, tool misuse, and data exfiltration; document findings and drive each issue through to remediation and closure. • Build and iterate on guardrail logic, including input/output filtering, tool-boundary constraints, action validation, sensitive-data redaction, and policy prompting. • Integrate safety checks into CI/CD and runtime so that unsafe behavior is intercepted before it reaches users. • Perform threat modeling for agentic scenarios: tool-call boundaries, sandbox isolation, and least-privilege access, with particular attention to preventing agents from exfiltrating data or executing irreversible actions through chained tool calls. • Conduct safety reviews of reinforcement-learning (RL) environments and trajectory data, partnering with environment and agent engineering teams to embed safety constraints directly into the environments themselves. • Instrument AI features for safety with structured logging, tracing, and metrics, enabling detection of unsafe patterns and regressions in production. • Prepare evidence for governance reviews—test reports, evaluation summaries, and mitigation validation—aligned with internal Responsible AI standards. • Collaborate with Product and UX to improve safety interactions (warnings, confirmations, refusal messaging, and feedback collection), and align evaluation goals with the Research and Data teams.

🎯 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 with the ability to write production-grade code (primarily Python), beyond scripting or notebook prototyping. • Solid understanding of LLMs and ML: how models work, prompt engineering, and the safety implications of fine-tuning and RAG (e.g., unsafe retrieval, tool misuse, and data exfiltration). • A security mindset with demonstrated threat-modeling ability; able to threat-model AI workflows and familiar with the fundamentals of access control, data retention, and incident response. • Familiarity with the LLM attack surface—prompt injection, jailbreaks, data poisoning, and supply-chain risk—and working knowledge of the OWASP LLM Top 10. • Hands-on experience with at least one of safety evaluation or red teaming, with the ability to walk through a real finding and how it was remediated.

🏖️ Benefits

• Health insurance • Paid time off • Flexible work arrangements • Professional development • Stock options