Liberty Mutual Insurance
Overview
2 days ago Be among the first 25 applicants Liberty Mutual Insurance provided pay range. This range is provided by Liberty Mutual Insurance. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range: $175,000.00/yr - $315,000.00/yr Job Introduction
The Security Architecture & Innovation team within the Global Cybersecurity (GCS) organization is seeking a seasoned GenAI Security Platform Architect with expertise in securing AI/ML systems and GenAI applications. The candidate will define and drive the security architecture, controls, and governance for our AI platforms, models, and AI-enabled products. This role partners closely with Data Science, Enterprise Data & Analytics Technology, MLOps, Platform/Cloud, Legal/Privacy, and Global Cybersecurity Governance Risk and Compliance to design secure-by-design AI solutions that are resilient to adversarial threats and meet evolving regulatory requirements. Responsibilities
Define and own the end-to-end security architecture for AI/ML systems (training, fine-tuning, inference/serving, RAG, agents, and integrations). Develop and maintain reference architectures and guardrails for common AI patterns (e.g., RAG with vector databases, multi-agent workflows/orchestration, LLM API integrations, on-prem vs. cloud model hosting). Build and maintain an AI security controls library mapped to frameworks (e.g. NIST AI RMF, OWASP Top 10 for LLM Apps, MITRE ATLAS). Establish risk appetite and control requirements across the AI lifecycle; perform design reviews and signoffs for AI initiatives. Define security baselines, secure configurations, and kill-switch/rollback strategies for AI components. Continuously assess threat landscape and update risk models specific to AI/ML, GenAI, and insurance sector adversaries. Secure AI development and MLOps; integrate security into the ML/LLM SDLC and CI/CD pipelines (dataset curation, feature engineering, model training, evaluation, packaging, registry, deployment). Partner across Global Cybersecurity, Global Digital Solutions (Cloud/Platforms/Infrastructure/Endpoint), and Liberty IT to enforce least privilege, secrets management, and policy-as-code for AI pipelines and serving infrastructure. Champion DevSecOps automation for AI projects by embedding security controls and testing directly into development pipelines. Advise on adversarial robustness and safety; coordinate testing and safety evaluations; validate defenses (input/output filtering, content moderation, prompt hardening, retrieval sanitization). Drive monitoring for model drift, anomaly detection, and harmful output prevention; develop response playbooks for AI incidents. Ensure data minimization, classification, encryption, and access controls for training and inference data (incl. embeddings and vector stores); ensure compliance with global privacy regulations (CCPA, NYDFS, GDPR, etc.). Recommend/consult with GRC on AI security governance, policies, and standards; define measurable KPIs and support vendor/security assessments for AI services and model providers. Evaluate and select AI security tools; manage POCs and guide build-vs-buy decisions; mentor teams on best practices in AI/ML security. Qualifications
Bachelor’s degree in Computer Science, Engineering, Information Security, or equivalent experience. Minimum 8+ years in Cybersecurity with 3+ years focused on securing AI/ML systems or GenAI applications in production. CISSP certification required. Deep technical experience designing secure architectures for ML pipelines and MLOps platforms; GenAI workloads; cloud-native environments. Strong knowledge of AI-specific threats and mitigations and practical familiarity with security frameworks and standards (NIST AI RMF, OWASP Top 10, MITRE ATT&CK/ATLAS). Hands-on experience with identity and access controls, secrets management, encryption, monitoring/logging for AI systems. Excellent communication skills and ability to influence architecture and risk decisions across engineering, product, and executive stakeholders. Preferred Qualifications
Experience with enterprise GenAI platforms and tools (MLOps and LLM/GenAI tools listed in the original description). Observability tools and AI eval frameworks; red-team tooling. Advanced degree (MS/PhD) in Security, ML/AI, or related field is a plus. How We Work
Partner-first: embed with Data Science, MLOps, and Product teams to enable speed with safety. Automate-by-default: codify controls in pipelines and platforms rather than relying on manual gates. Measurable risk management: define clear control objectives, metrics, and continuous improvement loops. About Us
Pay Philosophy: The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role. Some roles may include commission and/or bonus earnings at rates that vary based on multiple factors set forth in the compensation plan for the role. Liberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran\'s status, pregnancy, genetic information or on any basis prohibited by federal, state or local law. This description preserves the intent but omits extraneous site-specific notices. Equity and Accessibility
Liberty Mutual is committed to fostering an inclusive environment where all backgrounds can build long and meaningful careers. We encourage employee feedback and support our Employee Resource Groups (ERGs). For benefits information, visit: https://LMI.co/Benefits
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2 days ago Be among the first 25 applicants Liberty Mutual Insurance provided pay range. This range is provided by Liberty Mutual Insurance. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range: $175,000.00/yr - $315,000.00/yr Job Introduction
The Security Architecture & Innovation team within the Global Cybersecurity (GCS) organization is seeking a seasoned GenAI Security Platform Architect with expertise in securing AI/ML systems and GenAI applications. The candidate will define and drive the security architecture, controls, and governance for our AI platforms, models, and AI-enabled products. This role partners closely with Data Science, Enterprise Data & Analytics Technology, MLOps, Platform/Cloud, Legal/Privacy, and Global Cybersecurity Governance Risk and Compliance to design secure-by-design AI solutions that are resilient to adversarial threats and meet evolving regulatory requirements. Responsibilities
Define and own the end-to-end security architecture for AI/ML systems (training, fine-tuning, inference/serving, RAG, agents, and integrations). Develop and maintain reference architectures and guardrails for common AI patterns (e.g., RAG with vector databases, multi-agent workflows/orchestration, LLM API integrations, on-prem vs. cloud model hosting). Build and maintain an AI security controls library mapped to frameworks (e.g. NIST AI RMF, OWASP Top 10 for LLM Apps, MITRE ATLAS). Establish risk appetite and control requirements across the AI lifecycle; perform design reviews and signoffs for AI initiatives. Define security baselines, secure configurations, and kill-switch/rollback strategies for AI components. Continuously assess threat landscape and update risk models specific to AI/ML, GenAI, and insurance sector adversaries. Secure AI development and MLOps; integrate security into the ML/LLM SDLC and CI/CD pipelines (dataset curation, feature engineering, model training, evaluation, packaging, registry, deployment). Partner across Global Cybersecurity, Global Digital Solutions (Cloud/Platforms/Infrastructure/Endpoint), and Liberty IT to enforce least privilege, secrets management, and policy-as-code for AI pipelines and serving infrastructure. Champion DevSecOps automation for AI projects by embedding security controls and testing directly into development pipelines. Advise on adversarial robustness and safety; coordinate testing and safety evaluations; validate defenses (input/output filtering, content moderation, prompt hardening, retrieval sanitization). Drive monitoring for model drift, anomaly detection, and harmful output prevention; develop response playbooks for AI incidents. Ensure data minimization, classification, encryption, and access controls for training and inference data (incl. embeddings and vector stores); ensure compliance with global privacy regulations (CCPA, NYDFS, GDPR, etc.). Recommend/consult with GRC on AI security governance, policies, and standards; define measurable KPIs and support vendor/security assessments for AI services and model providers. Evaluate and select AI security tools; manage POCs and guide build-vs-buy decisions; mentor teams on best practices in AI/ML security. Qualifications
Bachelor’s degree in Computer Science, Engineering, Information Security, or equivalent experience. Minimum 8+ years in Cybersecurity with 3+ years focused on securing AI/ML systems or GenAI applications in production. CISSP certification required. Deep technical experience designing secure architectures for ML pipelines and MLOps platforms; GenAI workloads; cloud-native environments. Strong knowledge of AI-specific threats and mitigations and practical familiarity with security frameworks and standards (NIST AI RMF, OWASP Top 10, MITRE ATT&CK/ATLAS). Hands-on experience with identity and access controls, secrets management, encryption, monitoring/logging for AI systems. Excellent communication skills and ability to influence architecture and risk decisions across engineering, product, and executive stakeholders. Preferred Qualifications
Experience with enterprise GenAI platforms and tools (MLOps and LLM/GenAI tools listed in the original description). Observability tools and AI eval frameworks; red-team tooling. Advanced degree (MS/PhD) in Security, ML/AI, or related field is a plus. How We Work
Partner-first: embed with Data Science, MLOps, and Product teams to enable speed with safety. Automate-by-default: codify controls in pipelines and platforms rather than relying on manual gates. Measurable risk management: define clear control objectives, metrics, and continuous improvement loops. About Us
Pay Philosophy: The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role. Some roles may include commission and/or bonus earnings at rates that vary based on multiple factors set forth in the compensation plan for the role. Liberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran\'s status, pregnancy, genetic information or on any basis prohibited by federal, state or local law. This description preserves the intent but omits extraneous site-specific notices. Equity and Accessibility
Liberty Mutual is committed to fostering an inclusive environment where all backgrounds can build long and meaningful careers. We encourage employee feedback and support our Employee Resource Groups (ERGs). For benefits information, visit: https://LMI.co/Benefits
#J-18808-Ljbffr