Engineering Division - Tech Risk Advisory -Vice President- Hyderabad/Bangalore

Bengaluru, IndiaOn-SiteFull-time12+ yrs experiencePosted 3w ago

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Job description

Responsibilities

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-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.

Job details are sourced from the employer's original posting.

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About the company

Goldman Sachs

Our team of engineers builds solutions to the most complex problems. We develop cutting-edge systems and processes that form the core of our key business and enable transactions to move in milliseconds. We provide real-time access to critical deal information and crunch billions of data points each day to inform firm-wide market insights and strategies. Team members have the opportunity to work at the forefront of technology innovation alongside industry leaders and make significant contributions to the field.

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Industry: Financial Services
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