Responsible AI Manager – Agentic AI Governance

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee the design, execution, and ongoing enhancement of governance strategies for agentic AI, collaborating with AI platform and product owners, data science teams, cybersecurity, legal, compliance, privacy, and quality departments.

• Convert Responsible AI expectations, organizational policies, and regulatory directives into practical governance criteria, operational workflows, and user guidance.

• Establish governance standards for technical controls and safeguards, including usage limitations, access management, human oversight, logging, anomaly detection, incident escalation, and mechanisms to pause, restrict, or deactivate AI functionalities when necessary.

• Track emerging AI technologies, risks, standards, and regulatory changes; evaluate their implications for the organization, and refine governance frameworks, standards, and controls to facilitate the responsible adoption of new AI capabilities.

• Create and uphold Responsible AI policies, standards, playbooks, procedures, guidance, and other control documentation to ensure consistent AI governance, regulatory compliance, and audit preparedness.

• Prepare materials for leadership, governance meetings, and cross-functional working groups, conveying risks, recommendations, decisions, implementation status, and governance results to support informed decision-making.

⛳️ Requirements

• Doctorate degree OR Master’s degree with 2 years of experience in AI/ML product development, MLOps/LLMOps, data science, software engineering, Responsible AI, AI governance, AI risk, or a related field OR Bachelor’s degree with 4 years of experience in AI/ML product development, MLOps/LLMOps, data science, software engineering, Responsible AI, AI governance, AI risk, or a related field OR Associate’s degree with 8 years of experience in AI/ML product development, MLOps/LLMOps, data science, software engineering, Responsible AI, AI governance, AI risk, or a related field OR High school diploma / GED with 10 years of experience in AI/ML product development, MLOps/LLMOps, data science, software engineering, Responsible AI, AI governance, AI risk, or a related field.

• Technical proficiency in AI/ML, generative AI, or agentic AI systems, including the capability to engage with technical teams on subjects such as model and agent behavior, logging and telemetry, tool usage, system prompts or instructions, configuration files, SDKs, APIs, and access controls.

• Strong grasp of AI risks and governance considerations, encompassing human oversight, accountability and transparency, privacy, validity and reliability, appropriate use, and fairness and bias mitigation.

• Awareness of AI regulatory, policy, or standards developments, including the EU AI Act and NIST AI Risk Management Framework.

• Capability to work efficiently across technical, legal, compliance, risk, cybersecurity, data science, and business teams, including the ability to influence stakeholders without direct control of the underlying technology platforms.

• Previous hands-on experience in data science, machine learning, software development, AI product development, MLOps, LLMOps, platform governance, or technical AI risk management.

• Experience with agentic AI, generative AI platforms, AI assistants, custom AI tools, workflow automation, AI-enabled software features, runtime monitoring, or enterprise AI product governance.

• Experience in translating Responsible AI, AI governance, risk, compliance, or regulatory expectations into actionable business processes, governance requirements, technical control expectations, guidance, or operating models.

• Previous employment in a regulated industry, such as biotechnology, pharmaceuticals, healthcare, financial services, or any environment with significant compliance, privacy, security, quality, or regulatory demands.

🏝️ Benefits

• A comprehensive employee benefits package, featuring a Retirement and Savings Plan with generous company contributions.

• Group medical, dental, and vision coverage.

• Life and disability insurance.

• Flexible spending accounts.

• A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan.

• Stock-based long-term incentives.

• Award-winning time-off plans.

• Flexible work models where feasible.