Job responsibilities

• Leads and scale a globally distributed security engineering organization delivering high‑impact platforms and services across the firm
• Owns the strategy, execution, and lifecycle management of AI/ML products t and Drive security platform adoption by partnering with application, infrastructure, and product teams to embed controls into developer and operational workflows
• Influences peer leaders and senior stakeholders across the business, product, and technology teams
• Holds accountability for decisions that influence teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures
• Delivers technical solutions that can be leveraged across multiple businesses and domains
• Influences peer leaders and senior stakeholders across the business, product, and technology teams
• Develops and executes the function’s objectives and is responsible for outcomes
• Holds responsibility for staffing, budget, and relevant profit and loss
• Champions the firm’s culture of diversity, opportunity, inclusion, and respect
• Leads the execution and continuous improvement of information risk and control strategies to secure Data & AI/ML services in public cloud
• Conduct and oversee risk-based assessments of technology controls for Data & AI/ML cloud services, platforms, and architecture.

Required qualifications, capabilities, and skills

• Experience running teams of engineers that deliver security solutions operations on cloud-based platforms and applications
• Experience building security engineering products and solutions for public cloud-based applications and infrastructure
• Experience developing and leading cross-functional teams of technologists
• Experience hiring, developing, and recognizing talent
• Experience leading a product as a product owner or product manager
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support cybersecurity architecture and engineering workflows with strong validation habits and awareness of data sensitivity.
• Ability to assess and validate AI-assisted security recommendations and AI-enabled design patterns before adoption, escalating uncertainty and ensuring outcomes align to security, resiliency, and auditability expectations.
• Drives reuse-first adoption of AI-assisted security validation within SDLC/toolchain routines, improving control testing and remediation quality with traceability/auditability and resiliency expectations.

• Uses enterprise-authorized AI capabilities within the work environment to accelerate cybersecurity architecture analysis, threat/risk assessment, and roadmap decisioning, validating outputs and handling data according to sensitivity and security requirements.

   

• Experience building internal developer or security platforms within large, regulated enterprises

• Familiarity with secure software development lifecycles and product security operating models

• Experience integrating security controls into CI/CD, cloud, and infrastructure platforms

• Background in modern detection, prevention, or endpoint protection technologies

• Strong understanding of risk‑based security decisioning at enterprise scale

• Practical experience and knowledge in cloud security concepts and best practices including IAM, encryption, network security, logging etc.
• Hands on experience in AWS focusing on security

• Demonstrable interest and experience in Data Analytics & AI/ML including Generative AI and LLMs