DevSecOps Engineer – Industrial AI Platform Role Summary
You’ll own security implementation across our AI deployment pipelines – from AWS EC2 development environments to air-gapped industrial sites. This hands-on role combines security engineering, infrastructure automation, and operational reliability for a platform deploying mission-critical ML models at the edge.
Key Responsibilities
Infrastructure Security Automation
- Develop and maintain OpenTofu modules for consistent VM provisioning across environments
- Harden EC2 and on-prem VM templates with Ansible security playbooks
- Implement least-privilege IAM policies and secure network configurations
- Design secure bootstrapping processes for production environments
Kubernetes Deployment Security
- Secure our K3s clusters with proper pod security policies and network isolation
- Implement robust RBAC models with granular permissions
- Design secure inter-service communication patterns
- Build security monitoring for cluster components and workloads
CI/CD Pipeline Hardening
- Integrate automated security scanning into build pipelines (container scanning, SCA, SAST)
- Implement secure artifact management with signing and verification
- Build proper secrets management for deployment pipelines
- Establish secure container base images and build processes
Operational Security & Reliability
- Design secure update mechanisms for air-gapped environments
- Implement monitoring, alerting and incident response automation
- Build comprehensive logging and audit trails across environments
- Develop metrics for tracking security and reliability KPIs
Security Reporting & Governance
- Create security dashboards for visibility into system security posture
- Build automated compliance validation for industrial requirements
- Develop practical security documentation and runbooks
- Run internal security reviews and share findings with engineering teams
Tech Stack
- Kubernetes (K3s for edge deployment, Kind for local dev, EKS for cloud)
- OpenTofu (planned) and Ansible for infrastructure automation
- AWS EC2 for development/test environments, on-prem for production
- GitHub Actions for CI/CD pipelines
- Docker for containerisation
- Python and Bash for security tooling and automation
- SvelteKit for frontend
Requirements
Essential Skills & Experience:
- Strong experience with infrastructure-as-code security (Terraform/OpenTofu, Ansible)
- Hands-on Kubernetes security implementation (networking, RBAC, policies)
- Experience securing containerised workloads and build pipelines
- Practical security monitoring and alerting implementation
- Experience with Linux security controls including AppArmor profile development and enforcement
- Comfort working with Python, shell scripts, and CLI tooling
- Ability to balance security requirements with practical engineering trade-offs
- Experience with log aggregation and operational monitoring
Desirable Skills:
- Experience with industrial or air-gapped deployments
- Knowledge of ML/AI deployment security considerations
- Familiarity with regulated environments (finance, healthcare, industrial)
- Experience with zero-trust networking concepts
- Experience with Linux hardening for edge deployments
About You
- You’re hands-on – you code solutions rather than just pointing out problems
- You find pragmatic security solutions that work in the real world
- You can explain complex security concepts to people who don’t live in that world
- You balance “secure by default” with “needs to actually work”
- You’re comfortable diving into unfamiliar codebases to find and fix issues
#DevSecOps #Engineer
