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As the Senior Architect of AI Governance & Risk, you will lead the design and operationalization of Babel Street’s AI trust framework across safety, privacy, security, bias/fairness, and transparency. You will ensure their AI-enabled products—spanning LLM-powered workflows, agentic systems, and multimodal capabilities—are built and deployed with measurable controls, defensible documentation, and audit-ready evidence.
A core part of this role is to create, institutionalize, and operationalize Babel Street AI Principles—and translate them into the policies, engineering standards, delivery gates, customer assurances, and reporting artifacts that guide how we build and deploy AI across the company.
This role requires extensive partnership with Product, Engineering, Security (CISO), Legal/Privacy, and Customer Success teams. You will serve as the connective tissue between these functions, ensuring governance requirements are understood, adopted, and embedded into the AI lifecycle—from design through production monitoring and incident response.
The ideal candidate is execution-oriented with a focus on customer-facing outcomes. You will translate emerging AI policy and customer requirements into concrete engineering controls and reusable collateral that accelerates RFI/RFP responses, supports due diligence, and reduces risk without slowing product velocity.
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
Required
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.
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