Overview
Lead the security architecture for next-generation AI solutions, defining standards and patterns that protect AI models, data, pipelines and agentic systems across their lifecycle.
What you'll do
- Lead AI architectural activities and develop secure solution architectures across business and technology domains.
- Define AI security standards and best practices for protecting AI pipelines, datasets, models and infrastructure.
- Develop logical architecture designs and strategies to secure the organization's AI domain and infrastructure.
- Establish and evolve AI architecture governance frameworks, including methods, practices, standards and reusable architecture patterns.
- Assess the AI landscape, identifying and mitigating security risks across model training, deployment and operations.
- Evaluate AI security technologies and integrate appropriate security controls across AI platforms and Large Language Models.
- Secure AI and agentic systems against model poisoning, adversarial inputs, prompt injection, jailbreaking and emerging threats.
- Design Model Context Protocol servers, AI agent workflows, secure deployment architectures and AI gateway integrations.
- Build Python services, developer tools, integrations and AI security harnesses supporting secure software development.
- Collaborate with data scientists, engineers and DevOps teams to embed security throughout the AI development lifecycle.
What you'll need
- 12+ years of overall professional experience, including substantial experience across security, architecture, software development and AI security engineering.
- At least 5 years of security experience.
- 5 years in architecture.
- 5 years in development.
- 2+ years in AI security and engineering.
- Proven AI security architecture expertise covering training data, models, pipelines, deployed AI solutions, security policies, standards and architecture patterns.
- Strong knowledge of AI threats, risk identification, threat modeling, data privacy and defenses against adversarial and AI-based attacks.
- Hands-on experience securing Artificial Intelligence and Machine Learning applications across cloud platforms, with strong Amazon Web Services engineering and architecture expertise.
- Production experience with AI coding agents, Model Context Protocol servers, agent workflows, Python development, automated testing and AI gateway integrations.
Nice to have
- Security engineering or application security background, with experience evaluating and working with specialized AI security technologies.
- Experience building developer-facing command-line tools and working effectively in multi-vendor, global technology environments.
Details
- Location: Hyderabad.
- Hybrid work arrangement.
- Relocation support available.
Read the full description and apply on the company’s own careers page.