Cybersecurity AI Forward Deployed Engineer

The Cybersecurity AI Forward Deployed Engineer will be embedded inside a client’s enterprise to help secure AI systems in production. This production engineering role focuses on building security architecture, threat models, and hardened deployments for agentic AI outcomes across complex, multi-stakeholder environments.

Role Focus

Work on AI security as a forward deployed production engineer, enabling AI systems to be secure, governed, and resilient through agentic coding and security engineering delivery. This position is not a security consulting role, compliance advisory position, or penetration testing engagement.

Responsibilities

• Support AI security architecture and threat modeling for production agentic deployments across complex, multi-stakeholder environments, including LLM systems, multi-agent pipelines, RAG architectures, and MLOps infrastructure, owning security design from assessment through hardened deployment.
• Deliver hands-on security engineering using agentic coding tools as a primary build environment by building AI-powered detection systems, automated threat response tooling, security assessment frameworks, and governance automation using Claude Code, Cursor, or GitHub Copilot.
• Manage AI-specific threat surfaces at programme scale, applying controls such as OWASP LLM Top 10, prompt injection hardening, model extraction prevention, adversarial input defenses, and AI supply chain security across concurrent client workstreams.
• Architect and govern AI security controls across the enterprise stack, including identity and access for AI systems, data pipeline security, model serving security, and integration risk across AWS, Azure, or GCP.
• Assist with AI governance framework implementation for live production systems, applying EU AI Act, NIST AI RMF, and model risk management beyond theoretical compliance work.
• Support client CISO and CTO with AI reinvention security strategy by developing risk-adjusted investment cases, security architecture roadmaps, and AI governance operating models aligned to commercial outcomes.
• Define and publish reusable security patterns, playbooks, and accelerators to scale across multiple client engagements and grow the Secure AI practice.
• Participate in architecture design sessions, threat modeling workshops, and code-with sessions with client engineering and security leadership teams.

Requirements

• Minimum 3 years of engineering experience in production environments with cybersecurity depth in at least one area: AppSec, SecOps / detection engineering, cloud security, IAM, offensive security / penetration testing, or GRC.
• Minimum 1 year of hands-on experience designing and deploying agentic AI solutions in a production environment (theoretical familiarity is not sufficient).
• Minimum 3 years working with cloud platform security fundamentals for at least one provider: AWS, Azure, or GCP, including IAM, network security, secrets management, and AI service security configurations.
• Bachelor’s degree or equivalent (minimum 12 years work experience). If an Associate’s Degree is held, minimum 6 years work experience is required.
• Proven ability to communicate security risk in business terms, translating threat exposure into risk-adjusted investment rationale suitable for a CISO or CFO.

Technologies

• Claude Code, Cursor, GitHub Copilot
• OWASP LLM Top 10
• EU AI Act, NIST AI RMF
• AWS, Azure, GCP

Location and Compensation

Location: Morristown, NJ (onsite)

Salary: USD 59,100 - 235,100 per yearly

Benefits

• Medical, dental, vision, life, and long-term disability coverage
• 401(k) plan
• Bonus opportunities
• Paid holidays
• Paid time off

Travel

Travel may be required for this role, varying from 0 to 100% depending on business need and client requirements.