This on-site role is based in Walnut Creek, California, with a salary range of USD 87,400 to 305,000 per year. The Senior Cybersecurity Forward Deployed Engineer collaborates with client teams to secure and govern AI deployments, employing agentic coding to develop security tooling and governance. The position oversees AI security architecture, threat modeling, and governance across production enterprise AI stacks.
Responsibilities
- Lead AI security architecture and threat modeling for production, agentic deployments across complex client environments, including LLM systems, multi-agent pipelines, RAG architectures, and MLOps infrastructure, owning the security design from assessment to hardened deployment.
- Deliver hands-on security engineering using agentic coding tools as the primary build environment: create AI-powered detection systems, automated threat response tooling, security assessment frameworks, and governance automation using Claude Code, Cursor, or GitHub Copilot during delivery.
- Manage AI specific threat surfaces at program scale: implement OWASP LLM Top 10 controls, harden prompts against injection, prevent model extraction, defend against adversarial inputs, and secure AI supply chains across concurrent client workstreams.
- Architect and govern AI security controls across the enterprise stack: identity and access for AI systems, data pipeline security, model serving security, and cross-system integration risk across cloud platforms (AWS, Azure, or GCP).
- Lead the implementation of AI governance frameworks: EU AI Act, NIST AI RMF, and model risk management applied to live production systems, beyond theoretical compliance exercises.
- Shape security strategy for AI reinvention presented to client CISOs and CTOs: develop risk-adjusted investment cases, security architecture roadmaps, and AI governance operating models aligned to business outcomes.
- Define and publish reusable security patterns, playbooks, and accelerators that scale across multiple client engagements and expand the Secure AI practice.
- Lead architecture design sessions, threat modeling workshops, and code-with sessions with client engineering and security leadership teams.
Requirements
- Minimum of 8 years of engineering experience in production environments with deep cybersecurity expertise in at least one area such as Application Security, 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 production; theoretical familiarity does not qualify.
- Minimum 6 years of demonstrated 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 of experience 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 work experience (minimum 12 years); if holding an Associate’s Degree, a minimum of 6 years of work experience is required.
- Proven ability to translate security risk into business terms, articulating threat exposure as risk-adjusted investment rationale suitable for a CISO or CFO.
- People leadership experience: managing, developing, and performance-managing a team of engineers, including setting development plans and conducting career conversations.
Technologies
- Claude Code
- Cursor
- GitHub Copilot
- AWS
- Azure
- GCP
Benefits
- Medical
- Dental
- Vision
- Life
- Long-term disability coverage
- 401(k) plan
- Bonus opportunities
- Paid holidays
- Paid time off
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