AI Risk & Responsible AI Specialist

C-Serv•Portland, OR

About The Position

The Opportunity We are building a dedicated AI Red Team to rigorously test and harden enterprise-scale AI products deployed to some of the world’s largest organizations. Security testing is only part of enterprise AI assurance. We are seeking an AI Risk & Responsible AI Lead to design and operationalize structured evaluation frameworks across safety, bias, robustness, explainability, and data governance. This role ensures our AI systems are secure, trustworthy, measurable, and enterprise-ready. What You’ll Do Design and implement model evaluation frameworks across AI products Develop methodologies for: Bias and fairness testing Hallucination and reliability assessment Robustness and stress testing Safety benchmarking Evaluate training data governance practices Review RAG systems for retrieval accuracy and exposure risks Establish measurable risk metrics across AI deployments Align evaluation outputs with: NIST AI Risk Management Framework ISO 27701 privacy requirements Enterprise governance standards Produce structured, executive-ready documentation Partner with product and engineering teams to integrate risk mitigation strategies This role bridges AI engineering, governance, risk quantification and enterprise accountability.

Requirements

Core AI Evaluation Expertise Experience designing model evaluation frameworks Familiarity with bias detection methodologies Understanding of hallucination testing and reliability measurement Experience stress-testing LLM-based systems Strong Python and experimentation capabilities
Governance & Risk Fluency Knowledge of NIST AI RMF Familiarity with privacy-by-design principles Experience operating within ISO 27001 / SOC 2 environments Understanding of enterprise AI risk posture expectations
Analytical & Communication Strength Ability to translate model risk into business impact Strong documentation skills Comfortable presenting findings to executive audiences Systems-thinking mindset
Structured and methodical
Deeply curious about model behavior
Pragmatic about risk
Comfortable challenging assumptions
Independent and decisive
Able to operate at executive altitude without losing technical depth
You understand that AI risk is not just about being hacked — it’s about predictability, fairness, resilience, and trust.

Responsibilities

Design and implement model evaluation frameworks across AI products
Develop methodologies for: Bias and fairness testing, Hallucination and reliability assessment, Robustness and stress testing, Safety benchmarking
Evaluate training data governance practices
Review RAG systems for retrieval accuracy and exposure risks
Establish measurable risk metrics across AI deployments
Align evaluation outputs with: NIST AI Risk Management Framework, ISO 27701 privacy requirements, Enterprise governance standards
Produce structured, executive-ready documentation
Partner with product and engineering teams to integrate risk mitigation strategies