Senior AI Security Engineer - Secure ML Lifecycle

SRI Resources; Irving (TX); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Medical, dental, and vision coverage

401(k) with company match

Short-term disability

Life insurance with AD&D

Job summary

Cybersecurity Jobs is seeking an experienced Security Engineer to design and deliver security controls for AI systems across the full lifecycle—from secure model development to detection and incident response. You will define security requirements across model development, training, deployment, and monitoring, and lead threat modeling of AI systems and features.

You will establish secure-by-design patterns for model endpoints, prompts, RAG pipelines, and agent workflows.

Qualifications

• 8+ years in Information Security, or 5+ years in security engineering, app security, cloud security or detection engineering if no degree
• At least 3 years of AI Security experience
• Experience securing LLM-based apps, RAG systems, or agentic workflows
• Familiarity with adversarial ML concepts: prompt injection, model inversion, model extraction
• Hands-on experience with at least one programming language (Python preferred)
• Strong understanding of AI/LLMs, API security, identity, secrets management, and cloud controls
• Experience building security controls into CI/CD pipelines
• Proven ability to lead cross-functional security work with engineering and product teams
• Excellent ability to communicate complex tech to both technical and non-technical stakeholders
• Proven leadership to influence and drive change

Responsibilities

• Define security requirements across model development, training, deployment, and monitoring
• Threat model AI systems and features, including abuse and misuse scenarios
• Establish secure-by-design patterns for model endpoints, prompts, RAG pipelines, and agent workflows
• Validate controls for model access, rate limiting, tenant isolation, and secrets management
• Classify and control training data, fine-tuning data, prompts, and retrieved context
• Develop CI and CD checks for AI assets, including scanning, signing, and policy enforcement
• Create logging standards for model requests, responses, tool calls, and retrieval events
• Develop detections for prompt injection, data exfiltration attempts, model extraction signals, and anomalous usage
• Develop incident response playbooks for AI events, including containment and rollback plans
• Run security testing for AI features, including red teaming and structured adversarial testing
• Create practical AI security standards, patterns, and reference architectures
• Lead risk reviews for new AI features and vendor assessments for AI services
• Train engineering and data science teams on secure AI patterns and common attack paths

Skills

Leadership capabilities

Cross-functional collaboration

Communication

Threat modeling

Security engineering

Education

Bachelor's degree in Cybersecurity or related field

Master's degree in Cybersecurity or related field

Tools

AWS

Azure

GCP

Kubernetes

Docker

GitHub Actions

GitLab CI

Azure DevOps

Terraform

SIEM

EDR

WAF

API Gateways

Secrets Managers

Python

Vector Databases

Model Registries

ML Pipelines

Job description

Cybersecurity Jobs is seeking an experienced Security Engineer to design and deliver security controls for AI systems across the full lifecycle—from secure model development to detection and incident response. You will define security requirements across model development, training, deployment, and monitoring, and lead threat modeling of AI systems and features.

You will establish secure-by-design patterns for model endpoints, prompts, RAG pipelines, and agent workflows.