Cybersecurity Forward Deployed Engineer - FDE - Manager

Responsibilities

• Oversee AI security architecture and threat modeling for production agentic deployments in multi-stakeholder client environments, including LLM systems, multi-agent pipelines, RAG architectures, and MLOps infrastructure; own end-to-end security design from assessment to hardened deployment.
• Perform hands-on security engineering within an agentic coding workflow to build 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.
• Manage AI specific threat surfaces at program scale: implement OWASP LLM Top 10 controls, harden prompts, 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 AWS, Azure, or GCP.
• Drive the implementation of AI governance frameworks such as EU AI Act and NIST AI RMF, applying model risk management to live production systems.
• Translate AI security strategy for client CISO and CTO, developing risk-based investment cases, architecture roadmaps, and governance operating models aligned with business outcomes.
• Create and disseminate reusable security patterns, playbooks, and accelerators to scale across client engagements and expand the Secure AI practice.
• Lead architecture reviews, threat modeling workshops, and collaborative code-with sessions with client engineering and security leadership.

Requirements

• At least 8 years of engineering experience in production environments with deep expertise in one cyber security domain such as application security, SecOps / detection engineering, cloud security, IAM, offensive security / penetration testing, or GRC.
• A minimum of 1 year hands-on experience designing and deploying agentic AI solutions in production; theoretical familiarity does not qualify.
• Six years or more of end-to-end security delivery ownership in a client-embedded or production setting; internal advisory or compliance-only roles do not qualify.
• Six years of experience with cloud 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.

Technologies

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

Benefits

• Medical
• Dental
• Vision
• Life insurance
• Long-term disability insurance
• 401(k) plan
• Bonus opportunities
• Paid holidays
• Paid time off

The Work

Cybersecurity FDEs operate as part of Accenture’s Reinvention Delivery Engine (RDE) Pod, a small, persistent, outcome-oriented team aligned to a client’s business domain or AI program. The pod works in 90-day delivery cycles, owns end-to-end outcomes across build, deploy, and optimize, and embeds directly inside the client’s technology organization.

Professional Skills Requirements

• Ability to translate security risk into business terms that support risk-adjusted investment decisions a CISO or CFO would act on.
• People leadership: experience managing, developing, and performance-managing a team of engineers, setting individual development plans, and conducting career conversations.

Requesting an Accommodation

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Other Employment Statements

• Applicants in the US must have work authorization that does not require visa sponsorship.
• Candidates currently employed by a client of Accenture or an affiliated Accenture business may not be eligible.
• Criminal conviction history is not an automatic bar to employment and disclosure is not mandatory.
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