First seen by Alion on Oct 15, 2026.
In this role you will build the foundations of a secure AI program from the ground up, working at the intersection of security architecture, cloud engineering, and artificial intelligence. You will treat AI security as an engineering discipline — grounded in clear architecture, recognized frameworks, and well-defined controls — and translate it into concrete, actionable work that engineering teams can implement, test, and continuously improve. You will primarily work with AI and LLM-based workloads, including the newest models deployed in isolated cloud environments, defining how they are designed, deployed, monitored, and governed, with a strong focus on guardrails, threat models, isolation requirements, and logging and monitoring standards.
Zakres obowiązków
- Build the foundations of the AI-based security program, including the roadmap, governance, and approval processes
- Define how AI can be safely used for security testing, such as AI-assisted code scanning and vulnerability discovery, including validation of findings and their integration into the vulnerability management process
- Define the AI security architecture and select and adapt the most suitable AI security frameworks
- Design threat models for AI workloads and define security controls for AI environments
- Design reference architectures for secure AI platforms deployed across AWS and GCP
- Define secure operating principles, deployment standards, and isolation requirements for frontier models
- Design guardrails, along with monitoring and logging requirements for AI systems
- Translate architecture and standards into an implementation backlog for engineering teams and support its delivery
Wymagania
- 7+ years in security architecture or cloud security, designing and securing complex, multi-cloud environments
- Proven hands-on experience securing AI/ML and LLM-based systems, including data, model, and infrastructure layers, and implementing effective containment measures for security incidents
- Strong knowledge of AI-specific threats such as prompt injection, data leakage, model abuse, and agent/tool misuse
- Understanding of AI infrastructure components, including model hosting, vector databases, orchestration frameworks, and AI gateways
- Experience conducting security assessments, adversarial testing, threat modeling, or red-team style evaluations of AI systems
- Familiarity with AI security frameworks and standards, such as NIST AI RMF, OWASP Top 10 for LLM Applications, MITRE ATLAS, and ISO/IEC 42001
- Experience with threat modeling and designing security controls, guardrails, and isolation for complex workloads
- Solid cloud security background in GCP and/or AWS, including IAM, network isolation, containers, and logging
- Experience defining security telemetry and detection use cases and integrating logs into SIEM or real-time analytics platforms
- Ability to turn strategy into actionable engineering requirements
- Strong communication and stakeholder management skills, fluent English
Tech stack
- Security
- Cybersecurity
- Cloud security
- AI
- AWS
- GCP
- NIST
- OWASP
- ISO
- Python
- Stakeholder management

