Security Architect
Security Managed Services Associate Manager
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Full time
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Experience: 5-10 years
Job No. ATCI-5565442-S2027338
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Bengaluru
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Required Skill: Secure AI
Project Role : Security Architect
Project Role Description : Define the cloud security framework and architecture, ensuring it meets the business requirements and performance goals. Document the implementation of the cloud security controls and transition to cloud security-managed operations.
Must have skills : Secure AI
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
Seeking a forward-thinking professional with an AI-first mindset to design, develop, and deploy enterprise-grade solutions using Generative and Agentic AI frameworks that drive innovation, efficiency, and business transformation.
We are seeking an operationally strong AI Cloud Security Lead with 9+ years of experience and deep expertise in cloud security, security architecture, enterprise risk assessment, and secure design for AI/ML and GenAI ecosystems. This role is ideal for professionals who can lead security architecture for complex cloud-native and AI-enabled environments while driving consistently, secure adoption of modern AI capabilities across the organization. You will define and govern security architecture patterns for AI platforms, LLM applications, orchestration frameworks, model hosting environments, cloud integrations, and data pipelines, while strengthening risk assessment, architectural decision-making, and control consistency across multi-cloud ecosystems. The ideal candidate demonstrates strong leadership, advanced cloud and security architecture expertise, and a practical understanding of AI-specific risks such as data leakage, model misuse, over-privileged access, insecure integrations, workload isolation challenges, and cloud-native attack paths.
Roles & Responsibilities
Lead AI-driven solution design and delivery by applying GenAI and Agentic AI to address complex business challenges, automate processes, and integrate intelligent insights into enterprise workflows for measurable impact.
Lead security architecture and design reviews across AI enabled, GenAI, and cloud native platforms deployed across enterprise environments.
Define and enforce security architecture patterns and secure by design standards for AI, GenAI, and cloud native workloads.
Lead threat modeling and security risk assessments for complex AI ecosystems, including LLMs, orchestration frameworks, model hosting platforms, APIs, integrations, and supporting cloud services.
Drive mitigation strategies for AI specific threats such as model misuse, data leakage, supply chain compromise, insecure integrations, and over privileged access.
Provide architectural oversight for cloud security controls, including IAM, networking, encryption, secrets protection, workload isolation, and security monitoring.
Define and guide cloud native AI workload isolation and secure multi tenant architecture patterns, including separation boundaries for compute, storage, identity, inference endpoints, and supporting services.
Guide and review the implementation of confidential computing strategies for sensitive or regulated AI workloads where required.
Review and approve security designs for APIs, microservices, orchestration services, integrations, and third party AI platforms or hosted model providers.
Guide DevSecOps integration for AI workloads, including CI/CD security controls, infrastructure as code protections, container security, and secure deployment governance.
Partner with Security, Risk, Privacy, Legal, Platform, and Engineering teams to ensure regulatory, contractual, and enterprise policy alignment for AI and cloud deployments.
Act as an escalation point for high risk security findings, architectural trade offs, and design exceptions in AI and cloud environments.
Drive security governance through reusable architecture patterns, threat libraries, guidance notes, review frameworks, and enterprise security standards.
Communicate AI cloud security risks, architectural decisions, and residual risk considerations clearly to senior technical and business stakeholders.
Mentor junior practitioners by reviewing assessment quality, findings, risk articulation, and remediation recommendations.
Professional & Technical Skills
Strong grasp of Generative and Agentic AI, prompt engineering, and AI evaluation frameworks. Ability to align AI capabilities with business objectives while ensuring scalability, responsible use, and tangible value realization. The candidate should be AI Native.
9 to 13 years of experience in cloud security, security architecture, enterprise security, or related senior technical roles.
Deep expertise in multi-cloud security across AWS, Azure, and GCP.
Strong understanding of AI/ML and GenAI security risks, cloud-native threat surfaces, and secure architecture patterns for modern AI ecosystems.
Proven experience defining security standards, reference architectures, governance controls, and design review expectations at enterprise scale.
Strong knowledge of cloud security domains including IAM, network segmentation, encryption, secrets management, logging, monitoring, workload protection, and data security.
Experience performing threat modeling and architectural risk assessments for distributed systems, cloud services, APIs, and AI-enabled platforms.
Practical understanding of secure AI hosting patterns, model endpoint protection, orchestration security, integration trust boundaries, and AI workload isolation requirements.
Familiarity with secure multi-tenant architecture design and workload isolation strategies for AI and cloud-native environments.
Exposure to confidential computing, trusted execution approaches, or secure processing strategies for sensitive cloud and AI workloads.
Strong stakeholder management, advisory, communication, and architectural decision-making skills.
Ability to guide cross-functional teams including cloud engineering, platform, DevSecOps, privacy, and governance stakeholders.
Strong documentation skills for security architecture reviews, standards, design decisions, and risk acceptance guidance.
Preferred certifications include ISC2 CISSP (Certified Information Systems Security Professional), ISC2 CCSP (Certified Cloud Security Professional), ISACA CISM (Certified Information Security Manager), as well as advanced cloud security or architecture certifications across AWS, Azure, and GCP. Kubernetes-focused security credentials such as Certified Kubernetes Security Specialist (CKS) are also highly valued
Additional Information
Location: Bengaluru, Hyderabad, Pune, Chennai, Mumbai, Gurugram (Gurgaon), Jaipur
Employment Type – Full Time.
15yrs education details AI Powered Tech Talent
Project Role Description : Define the cloud security framework and architecture, ensuring it meets the business requirements and performance goals. Document the implementation of the cloud security controls and transition to cloud security-managed operations.
Must have skills : Secure AI
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
Seeking a forward-thinking professional with an AI-first mindset to design, develop, and deploy enterprise-grade solutions using Generative and Agentic AI frameworks that drive innovation, efficiency, and business transformation.
We are seeking an operationally strong AI Cloud Security Lead with 9+ years of experience and deep expertise in cloud security, security architecture, enterprise risk assessment, and secure design for AI/ML and GenAI ecosystems. This role is ideal for professionals who can lead security architecture for complex cloud-native and AI-enabled environments while driving consistently, secure adoption of modern AI capabilities across the organization. You will define and govern security architecture patterns for AI platforms, LLM applications, orchestration frameworks, model hosting environments, cloud integrations, and data pipelines, while strengthening risk assessment, architectural decision-making, and control consistency across multi-cloud ecosystems. The ideal candidate demonstrates strong leadership, advanced cloud and security architecture expertise, and a practical understanding of AI-specific risks such as data leakage, model misuse, over-privileged access, insecure integrations, workload isolation challenges, and cloud-native attack paths.
Roles & Responsibilities
Lead AI-driven solution design and delivery by applying GenAI and Agentic AI to address complex business challenges, automate processes, and integrate intelligent insights into enterprise workflows for measurable impact.
Lead security architecture and design reviews across AI enabled, GenAI, and cloud native platforms deployed across enterprise environments.
Define and enforce security architecture patterns and secure by design standards for AI, GenAI, and cloud native workloads.
Lead threat modeling and security risk assessments for complex AI ecosystems, including LLMs, orchestration frameworks, model hosting platforms, APIs, integrations, and supporting cloud services.
Drive mitigation strategies for AI specific threats such as model misuse, data leakage, supply chain compromise, insecure integrations, and over privileged access.
Provide architectural oversight for cloud security controls, including IAM, networking, encryption, secrets protection, workload isolation, and security monitoring.
Define and guide cloud native AI workload isolation and secure multi tenant architecture patterns, including separation boundaries for compute, storage, identity, inference endpoints, and supporting services.
Guide and review the implementation of confidential computing strategies for sensitive or regulated AI workloads where required.
Review and approve security designs for APIs, microservices, orchestration services, integrations, and third party AI platforms or hosted model providers.
Guide DevSecOps integration for AI workloads, including CI/CD security controls, infrastructure as code protections, container security, and secure deployment governance.
Partner with Security, Risk, Privacy, Legal, Platform, and Engineering teams to ensure regulatory, contractual, and enterprise policy alignment for AI and cloud deployments.
Act as an escalation point for high risk security findings, architectural trade offs, and design exceptions in AI and cloud environments.
Drive security governance through reusable architecture patterns, threat libraries, guidance notes, review frameworks, and enterprise security standards.
Communicate AI cloud security risks, architectural decisions, and residual risk considerations clearly to senior technical and business stakeholders.
Mentor junior practitioners by reviewing assessment quality, findings, risk articulation, and remediation recommendations.
Professional & Technical Skills
Strong grasp of Generative and Agentic AI, prompt engineering, and AI evaluation frameworks. Ability to align AI capabilities with business objectives while ensuring scalability, responsible use, and tangible value realization. The candidate should be AI Native.
9 to 13 years of experience in cloud security, security architecture, enterprise security, or related senior technical roles.
Deep expertise in multi-cloud security across AWS, Azure, and GCP.
Strong understanding of AI/ML and GenAI security risks, cloud-native threat surfaces, and secure architecture patterns for modern AI ecosystems.
Proven experience defining security standards, reference architectures, governance controls, and design review expectations at enterprise scale.
Strong knowledge of cloud security domains including IAM, network segmentation, encryption, secrets management, logging, monitoring, workload protection, and data security.
Experience performing threat modeling and architectural risk assessments for distributed systems, cloud services, APIs, and AI-enabled platforms.
Practical understanding of secure AI hosting patterns, model endpoint protection, orchestration security, integration trust boundaries, and AI workload isolation requirements.
Familiarity with secure multi-tenant architecture design and workload isolation strategies for AI and cloud-native environments.
Exposure to confidential computing, trusted execution approaches, or secure processing strategies for sensitive cloud and AI workloads.
Strong stakeholder management, advisory, communication, and architectural decision-making skills.
Ability to guide cross-functional teams including cloud engineering, platform, DevSecOps, privacy, and governance stakeholders.
Strong documentation skills for security architecture reviews, standards, design decisions, and risk acceptance guidance.
Preferred certifications include ISC2 CISSP (Certified Information Systems Security Professional), ISC2 CCSP (Certified Cloud Security Professional), ISACA CISM (Certified Information Security Manager), as well as advanced cloud security or architecture certifications across AWS, Azure, and GCP. Kubernetes-focused security credentials such as Certified Kubernetes Security Specialist (CKS) are also highly valued
Additional Information
Location: Bengaluru, Hyderabad, Pune, Chennai, Mumbai, Gurugram (Gurgaon), Jaipur
Employment Type – Full Time.
15yrs education details AI Powered Tech Talent
15 years full time education
Bengaluru
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