Cybersecurity Forward Deployed Engineer - FDE Senior Manager

Benefits and culture

This onsite role in Culver City, CA offers a competitive salary range of USD 122,700 to 366,300 per year and a comprehensive benefits package. You’ll have medical, dental, vision, life, and long-term disability coverage, plus a 401(k) plan and bonus opportunities. The position also provides paid holidays and paid time off. The environment emphasizes practical impact, cross-functional collaboration, and ongoing professional development within a team that values hands-on delivery and customer outcomes.

Responsibilities

• Lead AI security architecture and threat modeling for production agentic deployments across complex multi-stakeholder client environments, including LLM systems, multi-agent pipelines, RAG architectures, and MLOps infrastructure, owning the full security design from assessment through hardened deployment.
• Perform hands-on security engineering using agentic coding tools as the primary build environment, creating AI-powered detection systems, automated threat response tooling, security assessment frameworks, and governance automation using Claude Code, Cursor, or GitHub Copilot in daily delivery practice.
• Own AI-specific threat surface management at program scale, covering OWASP LLM Top 10 controls, 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 multi-system integration risk across cloud platforms (AWS, Azure, or GCP).
• Lead AI governance framework implementation, applying EU AI Act, NIST AI RMF, and model risk management to live production systems rather than theoretical exercises.
• Shape AI reinvention security strategy for client CISO and CTO, building 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 that scale across client engagements and support the growth of the Secure AI practice.
• Lead architecture design sessions, threat modeling workshops, and code-with sessions with client engineering and security leadership teams.
• Provide cybersecurity domain expertise in at least one discipline (AppSec, SecOps, IAM, cloud, GRC, or offensive security).
• Support proposals and SOW development, solution shaping, and client commercial engagement.
• Facilitate executive workshops and communicate with C-suite and CISO-level stakeholders.
• Apply structured analytical thinking and hypothesis-driven problem decomposition to security challenges.
• Lead and coach a team of engineers and consultants through delivery, fostering development and performance.

Requirements

• Minimum of 10 years of engineering experience in production environments with deep cybersecurity expertise in at least one area: AppSec, SecOps / detection engineering, cloud security, IAM, offensive security / penetration testing, or GRC.
• Minimum 2 years of hands-on experience designing and deploying agentic AI solutions in production; theoretical familiarity does not qualify.
• Minimum 8 years of end-to-end security delivery ownership experience in a client-embedded or production environment; internal advisory or compliance-only roles do not qualify.
• Minimum 8 years working with cloud platform security fundamentals across at least one provider (AWS, Azure, or GCP): IAM, network security, secrets management, and AI service security configurations.
• Bachelor's degree or equivalent (minimum 12 years) work experience. If Associate’s Degree, must have minimum 6 years work experience.

Technologies

• Claude Code
• Cursor
• GitHub Copilot
• AWS
• Azure
• GCP