Engineer, AI — Agent Risk & Remediation

Job Responsibilities

• Build the crawling agents that scan every agent in the enterprise - built by any team - for those needing attention: deprecating models, token overruns, policy drift, updates due.
• Risk-tier what is found, using the tiers and criteria Safety Standards defines.
• Build enterprise-scale remediation automation that pushes safe fixes across the population where the tier allows.
• Route what can't be auto-fixed to each agent's owner and follow up to closure against SLA; SRE is one such owner, for the agents your team builds.
• Collaborate with cross-functional teams to ensure effective integration and functionality of AI systems
• Also responsible for other duties/projects as assigned by business management as needed

Education and Work Experience

• Bachelor's Degree plus 3 years of related work experience
• OR advanced degree with 1 year of related work experience
• OR a combination of education and experience deemed equivalent (Required)
• Acceptable areas of study include Computer Science, Engineering, Artificial Intelligence, Data Science, or a Related Field (Preferred)
• 2-4+ years Developing and deploying machine learning models, including fine-tuning and prompt engineering (Preferred)
• 2-4+ years Experience with AI tools and software development using programming languages such as Python or R (Preferred)
• 2-4+ years Collaborating with cross-functional teams to integrate AI solutions into business workflows (Preferred)

Required Knowledge, Skills and Abilities

• Cloud Computing
• Collaboration
• Customer-Focused
• Data Analysis
• Data Management
• Data Modeling
• Model Tuning
• Prompt Engineering
• Enterprise-Scale Scanning & Automation
• Remediation Automation
• Risk Tiering & Prioritization

Licenses and Certifications

• Certified Analytics Professional (CAP): Validates expertise in data analytics processes, including the ability to model and interpret complex data. (Preferred)
• Machine Learning Certification: Demonstrates proficiency in machine learning techniques and applications, relevant for developing AI models. (Preferred)
• Certified Data Scientist (CDS): Endorses skills in data science and its application in AI modeling. (Preferred)