TL;DR
AI Security Engineer (Fintech): Supporting the Cybersecurity, Engineering, and Data Science organizations by ensuring that AI/ML and generative AI systems are secure, resilient, and compliant. Focus on application security, AI/ML risk, and cloud-native security engineering to advance InvoiceCloud’s AI-first strategy.
Location: US-Remote
Company
InvoiceCloud is a fast-growing fintech leader recognized with 20 major awards in 2025.
What you will do
- Lead AI Security Architecture & Secure Design initiatives.
- Conduct structured Threat Modeling & Risk Assessment exercises for generative AI, RAG, and agent-based systems.
- Define and operationalize Monitoring, Detection & Incident Response capabilities for AI systems.
- Establish and formalize AI Governance, Privacy & Third-Party Risk requirements.
- Integrate Secure MLOps / MLSecOps controls into AI delivery pipelines.
- Build and scale AI Security Testing & Red Teaming workflows.
Requirements
- Bachelor’s degree in Computer Science, Cybersecurity, Engineering, Data Science, or related field (or equivalent practical experience).
- 5+ years of experience in security engineering, application/product security, cloud security, or DevSecOps.
- 2+ years of experience building or securing AI/ML systems (including LLM-based applications) in production environments.
- Strong understanding of AI/ML threats and defenses.
- Experience integrating security into CI/CD and MLOps pipelines.
- Proficiency with cloud platforms (AWS and Azure), container security, IAM, network segmentation, key management, and secrets management.
Nice to have
- Familiarity with industry guidance such as OWASP GenAI/Top 10 for LLM Applications, MITRE ATLAS, and/or NIST AI RMF preferred.
- Relevant certifications such as CISSP, CSSLP, CCSP, Azure Security certifications, or GIAC certifications preferred.
Culture & Benefits
- Award-winning, purpose-driven environment where top talent thrives.
- Committed to providing equal employment opportunities to all employees and applicants.