AI Platform Security Engineer

About Fluid AI Fluid AI is a specialized cutting-edge Gen AI company with an enterprise level GPT product that caters to corporates. We are one of the pioneering companies in the field of Artificial Intelligence. Our GPT product allows businesses to increase their productivity by getting assistance in all key functions including sales and marketing, operations, customer support etc. Our founders, Abhinav & Raghav Aggarwal have been on the cover of the Forbes Magazine as well as on the Forbes 30 Under 30 list and the Fortune 40 Under 40 list. Abhinav & Raghav have appeared on numerous TV channels including NDTV, CNBC TV18, ET NOW etc. They are the authors of the world's first ever book written by an AI Algorithm. They have worked with Warren Buffet to create a digital human avatar for the Forbes centennial issue. About the Role Fluid AI is looking for an AI Platform Security Engineer to help secure our enterprise Agentic AI Platform. You'll work across the entire technology stack, including Python services, JavaScript applications, Kubernetes, Docker containers, autonomous AI agents, APIs, databases, CI/CD pipelines, and cloud infrastructure, to identify, investigate, and fix security vulnerabilities before they reach production. This is a hands-on engineering role focused on building secure systems, improving the platform's security posture, and enabling our engineering teams to build secure-by-default AI applications. Responsibilities Identify, investigate, and remediate security vulnerabilities across the Fluid AI Platform Perform security reviews of Python, JavaScript/TypeScript, and infrastructure code Secure autonomous AI agents, workflows, and tool integrations against common attack vectors Harden Kubernetes clusters, Docker containers, and deployment infrastructure Implement secure authentication, authorization, secrets management, and least-privilege access controls Build automated security checks into CI/CD pipelines Perform dependency analysis and remediate vulnerable packages Conduct threat modeling for new platform features and AI capabilities Improve platform security through continuous testing, automation, and monitoring Required Skills 1–4 years of software engineering or security engineering experience Strong understanding of Python and JavaScript/TypeScript Experience working with Linux, Docker, and Kubernetes Good understanding of common web application vulnerabilities (OWASP Top 10) Familiarity with authentication, APIs, networking, and secure software development Strong debugging and problem-solving skills Good to Have Experience with SAST, DAST, container security, or vulnerability scanning Knowledge of Kubernetes security, RBAC, network policies, and admission controllers Experience with OpenTelemetry or security monitoring Familiarity with cloud platforms such as AWS, Azure, or GCP Experience securing LLMs, MCP servers, autonomous agents, or AI applications Exposure to penetration testing or Capture the Flag (CTF)…