Lead the design and implementation of security controls across AWS, EKS/Kubernetes, CI/CD (Jenkins, GitHub Actions, ArgoCD), and AI/agentic engineering workflows.
Own threat modelling, risk assessments, and security architecture reviews across infrastructure, applications, and AI-driven systems.
Drive vulnerability management end-to-end — including code, infrastructure, and AI-generated artifacts — using tools such as NewRelic, Bugsnag, and security scanners.
Define and enforce secure coding and AI usage standards, including guardrails for LLMs, copilots, and automated workflows.
Build and operate security monitoring, alerting, and incident response capabilities, including detection and handling of AI/agent-related risks.
Evaluate and manage security and AI tooling (SAST/DAST, SIEM, EDR, secrets management), ensuring least-privilege access and secure integrations.
Harden infrastructure and data layers (Terraform, IAM, VPC, Cloudflare, Cassandra, Kafka, Redis), including protections against unauthorized or automated actions.
Drive compliance (SOC 2, ISO 27001) with a focus on auditability, data protection, and governance of AI systems.
Act as a security leader — educating teams, shaping best practices, and staying ahead of threats across AI, cloud, and Web3 (smart contracts, key management, bridges).
Partner with blockchain/product teams to mitigate risks in decentralized systems.
Requirements
5–8 years in security engineering across application, cloud, and infrastructure security.