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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Security Engineering - Vice President - **Company:** The Goldman Sachs Group Inc - **Location:** New York, NY, United States - **Salary:** $150,000.0 - $250,000.0 - **Contract:** Permanent contract - **Skills:** Kubernetes Security, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Bash Shell, Cloud Computing Security, Cloud Engineering, Cyber Security, Data Governance, Software Design Patterns, Identity and Access Management, Intrusion Detection and Prevention, Python (Programming Language), Key Management, Network Security, Machine Learning, Open Web Application Security, Windows PowerShell, Systems Development Life Cycle, Cloud Services, Azure Machine Learning, Systems Integration, Software Vulnerability Management, Data Logging, Scripting, Google Cloud, Cloud Platform System, Large Language Models, Software Security, Generative AI, Agentic-AI, National Institute of Standards and Technology Cybersecurity Framework, AI Platforms, Data Management, Machine Learning Operations, Prompt Injection, CIS Benchmarks, Oracle Cloud Infrastructure, Databricks, Vulnerability Analysis, Microservices - **Published:** October 10, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/87297930/1 ## About the Role * 12+ years of hands-on experience in cybersecurity, with depth spanning in the following domains: * Cloud Security: Architecting and assessing security for cloud-native and hybrid environments across major CSPs (AWS, Azure, GCP, OCI). * Security Engineering: Building security tooling, automation, detection capabilities, or secure-by-design systems at scale. * AI Engineering Security: Securing AI/ML systems, LLM-based applications, agentic pipelines, or ML infrastructure. * Cybersecurity Generalist: Broad cross-domain expertise including network security, identity and access management, threat modeling, vulnerability management, incident response, and compliance. * Strong development and scripting proficiency (Python, PowerShell, Bash, or similar) for automation, security tooling, and data analysis. * Deep, demonstrated knowledge of cloud security architecture across at least one major CSP (AWS strongly preferred), including IAM, network security, encryption/key management, workload/container security, and monitoring/logging. * Technical expertise in application security architecture, including secure-by-design patterns, threat modeling, and enterprise AppSec standards for web, API, and microservices environments. * Proven experience securing AI/ML systems or platforms, including familiarity with threats specific to LLMs, model pipelines, and AI supply chains. * Proven track record driving security initiatives across large, complex enterprise environments with cross-functional impact., * Experience in financial services or other highly regulated industries, with familiarity with relevant compliance frameworks. * Advanced knowledge of industry security frameworks and standards (e.g., NIST AI RMF, NIST CSF, ISO 27001, CIS Benchmarks, MITRE ATLAS, OWASP LLM Top 10). * Familiarity with AI/ML security frameworks including OWASP LLM Top 10, MITRE ATLAS, and NIST AI Risk Management Framework. * Strong leadership and communication skills to influence at the executive level, mentor technical teams, and represent security in cross-functional forums. * Relevant certifications across security and cloud domains (e.g., CISSP, CCSP, AWS Certified Security - Specialty, Azure Security Engineer * Associate, Google Cloud Professional Cloud Security Engineer, GIAC certifications). * Experience with MLOps, model deployment pipelines, and AI platform security (e.g., SageMaker, Vertex AI, Azure ML, Databricks). * Hands-on experience with red teaming, or adversarial testing of AI/ML systems ## Description * Conduct comprehensive cloud security assessments, evaluating designs, configurations, and implementations across major cloud service providers (CSPs) including AWS, Azure, and GCP. * Architect and drive enterprise-wide cloud security strategies, including baselines, guardrails, and secure design patterns for cloud-native and hybrid environments. * Identify and analyze potential security risks, vulnerabilities, and misconfigurations within cloud environments, AI/ML platforms, and applications. * Perform software architecture design reviews for cloud deployments, including AI/ML pipelines, LLM integrations, agentic frameworks, and data platforms. * Develop and enforce security controls for AI/ML systems, covering model security, data governance, prompt injection defenses, supply chain integrity, and inference infrastructure hardening. * Collaborate with AI engineering, platform, and development teams to embed security throughout the SDLC and CI/CD pipelines, including AI[1]specific development workflows. * Develop, evaluate, and document security measures, controls, and guardrails to protect data, applications, APIs, and infrastructure across cloud and AI environments. * Provide senior technical advisory services on cloud security, AI security, and security engineering to internal stakeholders, ensuring alignment with firm-wide security policies and industry best practices. * Develop and maintain scripts, automated solutions, and security tooling to streamline security processes, vulnerability identification, and compliance checks across cloud and AI environments. * Stay current on emerging threats across cloud, AI/ML, and security engineering domains, including adversarial ML techniques, cloud-native attack vectors, and evolving regulatory requirements. * Lead and mentor technical security teams; influence senior stakeholders and align security posture with business objectives. * Contribute to incident response and remediation efforts related to cloud security and AI security events as required.