What You Will Do
Secure the agentic AI platform
Own the multi-year security roadmap for our AI products, including agent workflows, MCP, RAG pipelines, and AI-enabled services.
Define and drive runtime security controls to protect against prompt injection, goal hijacking, unauthorized tool calls, data exfiltration, and other emerging AI threats.
Own the security architecture for agent sandboxing and isolated execution, ensuring untrusted code and tool outputs cannot impact the host environment or other tenants.
Build and lead a continuous AI red-team program focused on model, agent, and AI application security, including adversarial testing, data poisoning, model abuse, and privacy risks.
Own cloud and infrastructure security
Define and enforce cloud security standards across AWS, GCP, and Azure, including requirements for protecting sensitive customer data and supporting zero-data-retention commitments.
Establish secure identity and access models for workloads and AI agents, ensuring least-privilege access across cloud environments.
Drive Infrastructure-as-Code security and cloud security posture management to maintain a consistent security posture across global environments.
Partner with Security Operations, Engineering, and Cloud teams to improve cloud monitoring, detection, vulnerability management, and incident response.
Build the paved road for engineering
Build and drive an automated security toolchain integrated into CI/CD, covering application security testing, open-source dependencies, infrastructure, containers, and threat modeling.
Turn security and compliance requirements, including SOC 2, ISO 27001, and ISO 42001, into automated technical controls wherever possible.
Partner with Engineering leadership to define and maintain the security bar for products and infrastructure.
Establish risk-based remediation priorities so engineering teams focus on the vulnerabilities and exposures that matter most.
Lead the team
Report directly to the Head of Information Security and serve as a senior security leader across AI, product, cloud, and infrastructure security.
Partner closely with Product, Engineering, AI/R&D, Cloud, Infrastructure, and Compliance leadership to embed security into the development and delivery lifecycle.
Mentor and develop security engineers and emerging security leaders, helping them grow their technical, strategic, and leadership capabilities.
Build a strong security team and foster a culture of ownership, collaboration, and continuous improvement.
Drive an AI-first approach across security engineering and operations, using AI tools and automation to improve efficiency, automate repetitive work, accelerate delivery, and enable the team to operate at greater scale.
Identify opportunities to apply AI across security engineering, detection, vulnerability management, testing, automation, and operational processes while maintaining appropriate security and governance controls.
Translate emerging AI and cloud security risks into clear strategy, priorities, and investments.
Establish clear ownership, accountability, and measurable security outcomes across the team.
Required Qualifications
Security Leadership: 12+ years in cybersecurity/security engineering, including 4+ years leading engineering or security teams. Experience managing distributed teams across India and the U.S. is strongly preferred.
Hands-On Security Engineering: Strong hands-on experience securing production environments and writing or reviewing security automation using Python, Terraform, or equivalent. You must be able to design, build, review, and challenge technical security solutions.
Application & Product Security: Proven experience securing enterprise-scale applications, including secure design reviews, threat modeling, vulnerability management, and remediation with Engineering teams. Experience with Python, Go, or Node.js is preferred.
Cloud & Infrastructure Security: Deep experience with AWS, GCP, or Azure, including Kubernetes/container security, cloud architecture, workload identity, and least-privilege access.
AI Security: Practical understanding of LLM and agentic AI security, including prompt injection, insecure output handling, excessive agency, tool abuse, and data exposure. Strong security fundamentals with demonstrated AI security experience or self-directed learning are valued.
Communication & Leadership: Ability to explain technical risk and security strategy to executives, customers, auditors, and engineering teams, while working effectively across global teams and time zones.
Preferred Qualifications
Experience in a multi-tenant SaaS or AI platform company serving regulated enterprise customers (financial services, insurance, healthcare, or telecom).
Certifications such as CISSP, CCSP, or a cloud provider security certification.
Experience supporting enterprise customer security reviews, third-party risk assessments, or audit readiness.
Location preference
India - Bangalore
Uniphore is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.
For more information on how Uniphore uses AI to unify—and humanize—every enterprise experience, please visit www.uniphore.com.
