Cybersecurity AI Forward Deployed Engineer - FDE - Manager

The Cybersecurity AI Forward Deployed Engineer Manager role is embedded in client environments to help secure AI systems in production. The position focuses on hands‑on security engineering, including threat modeling, governance implementation, and measurable improvements to security posture across complex AI programs.

• Lead AI security architecture and threat modeling for production agentic deployments across complex, multi‑stakeholder client environments, owning the security design from assessment through hardened deployment for LLM systems, multi‑agent pipelines, RAG architectures, and MLOps infrastructure.
• Perform hands‑on security engineering using agentic coding tools as the primary build environment, including building AI‑powered detection systems, automated threat response tooling, security assessment frameworks, and governance automation with Claude Code
  , Cursor
  , or Git Hub Copilot
  .
• Own AI‑specific threat surface management at programme scale using OWASP LLM Top 10 controls, prompt injection hardening, model extraction prevention, adversarial input defenses, and AI supply chain security across concurrent client work streams.
• Architect and govern AI security controls across the enterprise stack, covering identity and access for AI systems, data pipeline security, model serving security, and integration risk across AWS, Azure, or GCP
  .
• Lead implementation of an AI governance framework for production systems, including EU AI Act
  , NIST AI RMF
  , and model risk management applied to live environments.
• Shape an AI reinvention security strategy in alignment with client CISO and CTO priorities 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 client engagements and grow the Secure AI practice.
• Run architecture design sessions, threat modeling workshops, and code‑with sessions with client engineering and security leadership teams.

• Minimum 8 years of engineering experience in production environments with cybersecurity discipline depth in at least one area:
  App Sec, Sec Ops and/or detection engineering, cloud security, IAM, offensive security and/or penetration testing, or GRC.
• Minimum 1 year of hands‑on experience designing and deploying agentic AI solutions in a production environment (the role requires practical delivery; theoretical familiarity is not sufficient).
• Minimum 6 years demonstrating end‑to‑end security delivery ownership in a client‑embedded or production environment; internal advisory or compliance‑only roles do not qualify.
• Minimum 6 years working with cloud platform security fundamentals across at least one provider:
  AWS, Azure, or GCP
  , including IAM, network security, secrets management, and AI service security configurations.
• Bachelor’s degree or equivalent with a minimum of 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 for a CISO or CFO.
• People leadership experience managing, developing, and performance‑managing a team of engineers, including setting individual development plans and conducting career conversations.

• Agentic coding tools: Claude Code, Cursor, Git Hub Copilot
• Security and governance: OWASP LLM Top 10, EU AI Act, NIST AI RMF
• Cloud platforms: AWS, Azure, GCP
• AI delivery contexts: LLM systems, multi‑agent pipelines, RAG architectures, MLOps infrastructure

Location: Austin, TX (onsite)

Salary range: USD 87, per…