Security Architect

Role summary

A Security Architect drives a security-first culture across platforms, products, and infrastructure as the primary security leader within Engineering. This role partners with Infrastructure, DevOps, Cloud, Product, and Development teams to embed security throughout the software development lifecycle and cloud operations. The ideal candidate combines strong Application Security and Infrastructure/Cloud Security expertise with the ability to challenge, influence, and guide teams toward secure architectural decisions while balancing business and delivery objectives. As the organization expands investments in AI-enabled platforms, intelligent automation, and agentic workflows, this role defines the security strategy and governance model for emerging AI technologies. Department: Engineering. Location: Noida.

Key responsibilities

• Security architecture & governance: Define and maintain enterprise-wide security architecture principles, standards, and best practices.
• Design review & approval: Review and approve application, platform, cloud, and infrastructure designs from a security perspective.
• Secure-by-design: Establish secure-by-design and secure-by-default engineering practices.
• Reference architectures: Develop and maintain security reference architectures, patterns, and reusable controls.
• SDLC security: Drive security throughout the Software Development Lifecycle (SDLC).
• Secure coding standards: Define and implement secure coding standards and security guardrails.
• Threat modeling: Lead threat modeling exercises for critical applications and platforms.
• Application security tooling: Oversee SAST, DAST, dependency scanning, container scanning, and software supply chain security initiatives.
• Vulnerability remediation: Partner with development teams to remediate vulnerabilities and security findings.
• Application design review: Review APIs, microservices, authentication mechanisms, and data protection strategies.
• Cloud-native security: Partner with Infrastructure and Cloud teams to design secure cloud-native architectures.
• Multi-cloud controls: Drive implementation of security controls across AWS, Azure, and hybrid environments.
• Network & perimeter security: Review network architecture, IAM, WAF, load balancers, VPNs, firewalls, and segmentation strategies.
• Infrastructure baselines: Establish security baselines for servers, containers, Kubernetes clusters, and cloud services.
• Policy & regulatory compliance: Ensure compliance with security policies, standards, and regulatory requirements.
• CI/CD security: Integrate security controls into CI/CD pipelines.
• Security automation: Drive automation of security testing and compliance validation.
• Security metrics: Define metrics, KPIs, and dashboards to measure security posture.
• Policy-as-Code: Promote Infrastructure-as-Code and Policy-as-Code security practices.
• Vulnerability management: Establish vulnerability management processes across applications and infrastructure.
• Risk-based prioritization: Prioritize remediation based on risk and business impact.
• Security risk assessments: Lead security reviews and risk assessments for new initiatives.
• Release sign-off: Provide security sign-off for production releases and critical architectural decisions.
• Engineering security leadership: Act as the primary security representative within Engineering.
• Cross-functional partnership: Partner closely with Infrastructure, DevOps, Enterprise Architecture, Product Management, and Engineering Leadership.
• Design challenge: Challenge designs and implementation decisions when security risks are identified.
• Security mentorship: Mentor engineering teams on security best practices.
• Security culture: Drive security awareness and cultivate a security-first engineering culture.
• AI security governance: Define security principles, standards, and governance frameworks for AI-enabled applications and agentic platforms.
• Agentic guardrails: Establish security guardrails for autonomous agents, intelligent workflows, and machine-to-machine interactions.
• LLM & AI risk assessment: Assess risks associated with Large Language Models (LLMs), AI services, model integrations, and third-party AI platforms.
• AI data & access controls: Develop controls around prompt security, data privacy, access management, context handling, and auditability.
• Secure AI adoption: Collaborate with Architecture and Engineering teams to implement secure AI adoption practices.
• AI workflow monitoring: Drive governance and monitoring mechanisms for AI-driven decision making and automated workflows.
• Emerging AI threats: Evaluate emerging AI security threats including prompt injection, data leakage, model abuse, excessive agent permissions, and supply chain vulnerabilities.
• Secure AI development standards: Partner with Engineering Excellence and Platform Engineering teams to establish secure AI development standards.
• AI-assisted development security: Provide architectural guidance for AI-assisted software development and secure use of developer productivity tools.

Requirements

• 8–10+ years of experience in Information Security, Security Architecture, Application Security, or Cloud Security.
• Strong hands-on experience with both Application Security and Infrastructure Security.
• Deep understanding of secure software development practices.
• Experience securing cloud environments such as AWS and/or Azure.
• Experience implementing security controls in CI/CD pipelines.
• Ability to perform threat modeling and security architecture reviews.
• Strong stakeholder management and influencing skills.
• Preferred: Security certifications such as CISSP, CCSP, CSSLP, AWS Security Specialty, Azure Security Engineer, TOGAF, or equivalent.
• Preferred: Experience in highly regulated environments.
• Preferred: Experience establishing security programs within engineering organizations.
• Preferred: Familiarity with compliance frameworks such as ISO 27001, SOC 2, PCI-DSS, NIST, or CIS Controls.
• Preferred: Exposure to Generative AI, Large Language Models (LLMs), Agentic AI frameworks, or intelligent automation platforms.
• Preferred: Understanding of AI security concepts including model security, prompt injection risks, data governance, and AI risk management.
• Preferred: Familiarity with emerging AI governance and security frameworks.

Benefits

• Best-in-class salary: We hire strong talent and compensate accordingly.
• Proximity Talks: Meet and learn from designers, engineers, product leaders, and AI practitioners.
• Continuous learning: Work with a world-class team and stay close to the latest in AI, engineering, and product development.
• High-impact work: Build AI-first systems and products used at scale by global clients.

About Us
Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media, and Entertainment companies in the world. We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore.
Since 2019, Proximity has built high-impact, scalable products used by millions of users every day. Today, we are a global team of engineers, designers, product managers, and experts solving complex problems and building cutting-edge technology at scale.