We are looking for a Senior Application Security Engineer to security architecture reviews, and code security assessments across microservices and cloud-native applications. This position will be full time and Remote.

What Youll Do

- Application Security Engineer with 5 to 8 years of experience
- Lead threat modeling, security architecture reviews, and code security assessments across microservices and cloud-native applications
- Perform SAST, DAST, SCA, and manual penetration testing on applications
- Identify, prioritize, and track remediation of vulnerabilities across the application portfolio
- Define and enforce secure coding standards and security best practices
- AI / LLM Security (AI Transformation Center Focus)
- Threat model AI systems identify and mitigate risks unique to LLM-powered applications: prompt injection, jailbreaking, model inversion, data poisoning, and training data leakage
- Conduct adversarial testing (red-teaming) of LLM and generative AI applications before production release
- Define and implement guardrails and content safety controls for LLM inputs/outputs (e.g., PII detection, toxicity filtering, output validation
- Evaluate and secure AI supply chain — third-party model APIs (OpenAI, Anthropic, Azure OpenAI), open-source model weights (Hugging Face), and fine-tuned models
- Establish policies around RAG (Retrieval-Augmented Generation) security — securing vector databases, embedding pipelines, and document ingestion workflows
- Implement controls against indirect prompt injection in agentic AI systems and multi-step LLM pipelines
- Assess AI agent security — tool call authorization, agent sandboxing, privilege boundaries, and action scope controls
- Ensure compliance with AI governance frameworks: ISO/IEC 42001, and internal AI usage policies




- Collaborate with Data Science and ML Engineering teams to secure model training pipelines, dataset storage, and model registries
- Drive AI incident response playbooks specific to model abuse, hallucination exploitation, and data exfiltration via LLM interface

What You'll Need

Required:

- DevSecOps & CI/CD Security
- Design and maintain DevSecOps pipelines integrating security gates into GitHub Actions workflows
- Automate SAST, container scanning, secrets detection, SCA, and AI model scanning within CI/CD pipelines
- Implement and manage Argo CD security policies, RBAC configurations, and deployment guardrails for GitOps workflows
- Enforce branch protection, signed commits, and secrets management in GitHub
- Integrate ML model integrity checks and artifact signing into AI deployment pipelines
- Container & Orchestration Security
- Harden Docker images — least-privilege, minimal base images, multi-stage builds, and image signing
- Secure Kubernetes clusters: RBAC, Pod Security Admission, Network Policies, OPA/Gatekeeper, and runtime security
- Isolate and sandbox AI inference workloads in Kubernetes — GPU node security, model server hardening (Triton, TorchServe, vLLM)
- Integrate container vulnerability scanning (Trivy, Grype, Snyk) into pipelines
- Security Operations & Governance
- Define security benchmarks aligned to ISO42001, NIST, OWASP (including OWASP LLM Top 10), and internal standards
- Collaborate with AI Engineering TEAM, Security and Risk Management Team, GRC Team, Infosec Team to shift security left

Physical Demands

- Ability to safely and successfully perform the essential job functions
- Sedentary work that involves sitting or remaining stationary most of the time with occasional need to move around the office to attend meetings, etc.
- Ability to conduct repetitive tasks on a computer, utilizing a mouse, keyboard, and monitor

📌 Senior Application Security Engineer (Bengaluru)
🏢 Cai Info India
📍 Bengaluru