About Cognizant Corporate
Cognizant Corporate is a global community united by a shared purpose: to make a meaningful impact. We are committed to excellence and driven by outcomes that matter. Collaboration is at the heart of how we work, and our forward-thinking mindset fuels continuous learning, innovation, and growth.
At Cognizant, careers transcend titles. We empower our people to think strategically, inspire others, and lead with purpose, always guided by our core values. Join us in shaping future of business. Could you be the one to make a difference?
About the role
As an AI Security Architect - Hyperscaler & Cloud AI Platforms , you will drive impactful contributions and focus on outcomes. You will be a key member of the AI Security Engineering & Enablement (AISE) team, collaborating with IT AI Architects, business unit solution teams, platform engineering teams, cloud security stakeholders, and hyperscaler architects. You will have the autonomy to lead, innovate, and improve workflows while upholding our commitment to quality and continuous learning. As a team of self-starters, you can work with impact with our vibrant people and culture while enjoying unmatched learning opportunities.
In this role, you will:
Own and maintain AI security reference architectures across Azure, AWS, and GCP AI service stacks, covering deployment patterns, network boundaries, identity, data flows, and guardrail integrations.
Define and maintain security baselines for AI platforms and services, including Azure OpenAI Service, Azure AI Foundry, Microsoft Copilot, Amazon Bedrock, SageMaker, Vertex AI, and GCP Gemini services.
Conduct STRIDE-based threat modelling for hyperscaler AI platforms and develop platform-specific security controls, standards, and implementation requirements.
Co-design secure AI solutions with IT AI Architects and delivery teams, providing architecture guidance, security blueprints, design reviews, and security sign-off as formal AISE deliverables.
Lead the development of AI-native security patterns, including identity architectures, data protection controls, AI supply chain security requirements, guardrail integration blueprints, and secure infrastructure deployment models.
Embrace our vibrant culture by striving for excellence, focusing on meaningful outcomes, and collaborating effectively. Prioritize quality, stay curious, and commit to continuous learning. Take ownership, build relationships, and focus on personal growth to drive business strategy and foster an inclusive culture, creating unmatched career opportunities and impactful work.
What you must have to be considered
10+ years of experience in cloud security architecture, including at least 3 years focused on AI/ML security within public cloud environments.
Deep hands-on experience with at least two of the following platforms: Azure AI Foundry, Azure OpenAI Service, Amazon Bedrock, or Vertex AI, including security configuration, network isolation, and identity architecture design.
Proven experience developing and implementing enterprise-scale cloud security reference architectures and technical security standards.
Strong threat modelling expertise using STRIDE and familiarity with MITRE ATLAS and OWASP LLM Top 10 as applied to cloud-hosted AI systems.
Experience designing identity architectures for AI workloads, including managed identities, OAuth 2.0 client credentials flows, workload identity federation, RBAC, and ABAC models.
Strong understanding of cloud data security controls, including encryption, data residency requirements, tokenization, VPC architectures, and private endpoint designs.
Experience addressing AI supply chain risks, including model provenance, software bills of materials (SBOM), dependency management, and model registry security.
Hands-on experience with Infrastructure as Code technologies such as Terraform, Bicep, or CloudFormation and integrating security requirements into infrastructure delivery pipelines.
A strong sense of ownership, desire to create meaningful outcomes, and passion for work that serves a greater good for customers, communities, or global challenges.
These will help you succeed
Experience implementing prompt injection defenses and guardrail controls at the platform or API gateway layer, including Azure APIM content filtering, Amazon Bedrock Guardrails, or Vertex AI safety controls.
Experience securing agentic AI workflows and multi-agent orchestration platforms, including LangGraph, AutoGen, or Semantic Kernel.
Industry certifications such as AZ-500, SC-100, AWS Security Specialty, GCP Professional Cloud Security Engineer, or equivalent credentials.
Familiarity with AI-specific detection and telemetry capabilities, including Azure Monitor AI logging, CloudTrail monitoring for Bedrock workloads, and Vertex AI audit logging.
Experience in consulting, managed security services, product security, or enterprise AI adoption programs operating at scale.
Ability to influence technical design decisions and collaborate effectively with hyperscaler solution architects and engineering teams.
Work model – Hybrid
We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a hybrid position requiring attendance at a Cognizant or client office as determined by business needs. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.
The working arrangements for this role are accurate as of the date of posting. This may change based on the project you’re engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.
We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role.
