- Company Name
- GALLO
- Job Title
- AI Security Engineer
- Job Description
-
Job Title: AI Security Engineer
Role Summary: Secure AI/ML systems through the entire lifecycle—embedding security controls, governance, and observability into training pipelines, inference services, and data flows. Implement AI‑specific risk mitigations, design monitoring, automate incident response, and collaborate with cross‑functional teams to align with NIST, ISO, and emerging regulations.
Expactations:
- Partner with Data & AI, IT, Legal, and Compliance to embed security into SDLC.
- Perform threat assessments (prompt injection, data poisoning, model inversion, leakage, adversarial attacks).
- Operate security tooling (SIEM, SOAR, AI‑security platforms) and automate workflows.
- Produce technical reports, metrics, and playbooks for leadership and stakeholders.
- Travel up to 5% for onboarding, training, and meetings.
Key Responsibilities:
- Define and enforce controls: model validation, access controls, provenance, bias mitigation, explainability, integrity checks.
- Design behavioral monitoring, drift and anomaly detection, and SIEM integrations.
- Develop security automation and AI‑driven incident response workflows.
- Conduct adversarial evaluations, penetration tests, and remediation plan management.
- Pilot model scanners, content‑safety solutions, and evaluate emerging AI security tools.
- Create training materials and playbooks for secure AI development.
Required Skills:
- Deep understanding of ML workflows (training/inference), data pipelines, and model architectures (LLMs, generative models).
- Secure coding practices, threat modeling, vulnerability assessment, penetration testing.
- Knowledge of AI‑specific threats and mitigations (prompt injection, model poisoning, data leakage, adversarial examples).
- Scripting/automation (Python, PowerShell) at intermediate level.
- Experience with Azure and AWS cloud platforms and native security controls.
- Advanced analytical, problem‑solving, and communication abilities.
- Ability to integrate security tooling with SIEM, SOAR, and observability stacks.
Required Education & Certifications:
- Bachelor’s in Computer Science, Information Security, Data Science (or 6 years experience with high school diploma).
- 2–4 years experience in cybersecurity, cloud security, or application security with AI/ML exposure.
- Certifications: CISSP, CISM, CEH, CCSK, or AI/ethics credentials preferred.
- Experience in agile environments and cross‑functional collaboration.