Engineering Division - Tech Risk Advisory -Vice President- Hyderabad

Goldman Sachs Group, Inc.; Hyderabad; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

Goldman Sachs Group, Inc. is seeking a senior cloud security and AI security leader in India to architect enterprise security for cloud environments and AI platforms. You will drive baselines, guardrails, threat modeling, and secure-by-design patterns across multi‑cloud and hybrid deployments.

You will mentor security teams, collaborate with AI engineering and platform groups, and develop tooling to automate security checks and governance across data, apps, and infrastructure.

Qualifications

• 12+ years in cybersecurity across cloud, security engineering, AI security, and generalist domains.
• Proficient in Python/PowerShell/Bash for automation.
• Deep cloud security architecture knowledge across at least one major CSP.
• Expertise in application security architecture and secure-by-design patterns.
• Experience securing AI/ML systems including LLM threats and AI supply chains.
• Proven track record driving security initiatives in large enterprises.

Responsibilities

• Conduct cloud security assessments across AWS, Azure, GCP, and other CSPs.
• Architect enterprise-wide cloud security baselines, guardrails, and patterns.
• Identify risks and misconfigurations in cloud environments, AI platforms, and apps.
• Review software architectures for cloud deployments including AI pipelines.
• Develop and enforce security controls for AI/ML systems and data governance.
• Collaborate with AI engineering, platform, and development teams to embed security in SDLC/CI/CD.
• Provide senior advisory services on cloud and AI security to stakeholders.
• Develop scripts and tooling to streamline vulnerability identification and compliance.
• Stay updated on threats and lead security teams to align with business goals.

Skills

Cloud security

Security engineering

AI/ML security

Cybersecurity generalist

Threat modeling

AppSec architecture

Scripting

Leadership

Job description

Responsibilities

• Conduct comprehensive cloud security assessments, evaluating designs, configurations, and implementations across major cloud serviceproviders (CSPs) including AWS, Azure, and GCP.
• Architect and drive enterprise-wide cloud security strategies, including baselines, guardrails, and secure design patterns for cloud-nativeand 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, supplychain 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-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.

Qualifications

Mandatory Requirements

• 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.

Preferred Qualifications

• 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.