AI Security Engineer

Role Summary

WWT Digital's AI-Native Security Feedback Loop offering (DIG-MLS-01) requires someone who sits at the exact intersection of AI engineering and security. You will help clients design, test, and harden AI agent deployments, build automated vulnerability feedback loops into SDLC workflows, and establish monitoring frameworks for model behavior in production. You will work with the Digital AI delivery team and WWT Security on joint engagements targeting enterprise engineering orgs deploying agentic AI at scale.

Responsibilities

• Assess AI and agent system architectures for security exposure — prompt injection paths, tool misuse, data exfiltration vectors, identity sprawl
• Design and implement NHI (Non-Human Identity) governance frameworks for AI agents, service accounts, and API credentials
• Build adversarial test suites for LLM-based applications — red‑team agents, jailbreak testing, context injection scenarios
• Integrate security feedback loops into AI development workflows: model evaluation gates, output monitoring, anomaly detection
• Define and implement MLSecOps practices: model signing, provenance, fine‑tune data validation
• Support OWASP Agentic Top 10 gap assessments alongside WWT Security architects
• Develop reusable patterns and accelerators that can be packaged into repeatable WWT offerings

Qualifications

• 4–7 years software or ML engineering, with at least 2–3 years focused on AI/ML security specifically
• Working knowledge of LLM application architecture: RAG, tool use, agent orchestration frameworks (LangChain, LlamaIndex, CrewAI, or similar)
• Hands‑on with adversarial ML techniques: prompt injection, data poisoning, model inversion, evasion attacks
• NHI security: service account hygiene, secrets rotation, OAuth/OIDC for machine‑to‑machine auth
• Security monitoring for AI in production: behavioral baselines, output anomaly detection, audit logging
• Experience with AI governance frameworks: NIST AI RMF, ISO/IEC 42001, emerging EU AI Act controls
• Can write code — Python at minimum, comfortable with LLM SDKs and agent frameworks
• Bonus: red‑team or penetration testing background applied specifically to AI systems
• Bonus: prior consulting experience; able to present to CISO and CTO audiences simultaneously

Salary

Estimated base pay range: $100,000 to $130,000 annually. Actual salary will be based on a variety of factors including shift, location, experience, skill set, performance, licensure and certification, and business needs. Certain positions may also be eligible for variable incentive compensation, such as bonuses or commissions.

Benefits

• Health and Wellbeing: Health, Dental, and Vision Care, Onsite Health Centers, Employee Assistance Program, Wellness program
• Financial Benefits: Competitive pay, Profit Sharing, 401k Plan with Company Matching, Life and Disability Insurance, Tuition Reimbursement
• Paid Time Off: PTO and Sick Leave (starting at 20 days per year) & Holidays (10 per year), Parental Leave, Military Leave, Bereavement
• Additional Perks: Nursing Mothers Benefits, Voluntary Legal, Pet Insurance, Employee Discount Program

If you have any questions or concerns about this posting, please email