Sr. Architect, AI Governance & Risk

This role spans three practical execution areas: 

AI Principles & Governance Architecture 

You will define Babel Street’s AI Principles and build the governance operating system that turns principles into action—standards, controls, documentation, and release gates that are implementable by engineering teams and measurable in production. 

AI Policy Intelligence, RFI/RFP Enablement & Reporting Collateral 

You will track and interpret emerging AI policy, regulations, and standards and assess their impact on Babel Street’s products and business. You will translate these requirements into roadmap implications, compliance strategies, and customer-ready collateral—enabling fast, consistent responses to RFIs/RFPs, security questionnaires, audits, and due diligence requests. 

Responsible AI Assurance Across Safety, Privacy, Security, Bias/Fairness & Transparency 

You will own the assurance posture for Babel Street AI— partnering with Engineering, Security, Legal/Privacy, and Product teams to ensure safety metrics, privacy controls, AI security testing, bias/fairness evaluation practices, and transparency artifacts (model/system cards) are defined, implemented, measured, and maintained over time. 

AI Strategy, Policy Intelligence & Business Impact 

• Create and operationalize Babel Street’s AI principles into enforceable engineering and product standards (e.g., secure-by-design patterns, privacy boundaries, oversight requirements, transparency expectations). 

• Monitor emerging AI policy, regulatory, and standards developments relevant to Babel Street markets and customer segments. 

• Partner with leadership to chart a pragmatic AI compliance and assurance strategy that supports growth and reduces friction in procurement cycles. 

AI Governance Program Design & Framework Development 

• Define and maintain Babel Street’s AI governance framework by embedding  AI principles into delivery workflows across the development lifecycle.   

• Partner with Engineering to maintain an AI model/system inventory, including third-party AI providers (e.g., GPT-4, Gemini, Claude), integrations, data touchpoints, and output constraints. 

• Define documentation standards for traceability: model lineage, evaluation results, monitoring plans, limitations, and intended/prohibited use. 

Customer Assurance: RFI/RFP Response, Due Diligence & Reporting 

• Ensure Babel Street AI Principles are reflected consistently in customer-facing commitments, product documentation, training materials, and reporting artifacts. 

• Lead the company’s responsible AI posture in AI-focused RFI/RFP responses, audit support, and customer due diligence—ensuring responses are consistent, evidence-backed, and defensible. 

• Create a repeatable evidence program (what we collect, how we maintain it, and how we produce it quickly and consistently). 

Safety & Reliability (Partner: Engineering, Product) 

• Partner with Engineering to define safety metrics (reliability, robustness, response times, bias correction, etc..) and ensure these are tracked and measured in production 

• Coordinate with Product to establish policies and procedures for AI safety, including documented response times for system failures 

• Lead the development of AI-specific Incident Response Procedures (IRPs) in partnership with Security and Engineering teams, ensuring readiness to address AI safety-related issues 

Privacy & Data Handling (Partner: Legal/Privacy, Engineering) 

• Partner with Legal/Privacy to define and enforce AI privacy requirements including data minimization, retention boundaries, and third-party data protection 

• Coordinate customer data usage positions: whether customer data is used for AI model training/improvement, and ensure opt-out mechanisms are clearly documented and enforceable 

• Lead privacy risk assessments for AI features and ensure data handling practices with third-party AI providers are documented and compliant (CCPA, ISO 42001, relevant regulations) 

Security & Audit (Partner: Security/CISO, Engineering) 

• Partner with Security (CISO) to establish AI security requirements, including access controls and employee/third-party access management to customer data 

• Coordinate internal and external AI security audits that address AI-specific vulnerabilities (prompt injection, jailbreaking, etc.) with clear remediation processes 

• Ensure output validation processes are in place to identify risks of unreliable or harmful content 

• 8+ years of experience across governance, risk, security, privacy, compliance, or systems architecture, including 3+ years supporting AI/ML-enabled systems in production. 

• Demonstrated ability to translate governance requirements into implementable controls and engineering practices (not policy-only work). 

• Strong understanding of AI governance frameworks and standards (e.g., NIST AI RMF, ISO/IEC 42001, ISO/IEC 23894) and ability to translate requirements into organizational processes 

• Experience producing customer-facing and audit-ready content: RFI/RFP responses, control narratives, assurance artifacts, and executive-ready summaries 

• Strong stakeholder management and influence skills; able to drive decisions, build consensus, and maintain accountability across multiple teams 

• Excellent written and verbal communication skills; able to craft clear, defensible positions for customers, executives, and internal teams 

Education

Bachelor’s degree  or equivalent experience in Computer Science, Engineering, Information Assurance, Data Science, Public Policy (with technical depth), or a related field required.