AI - Cybersecurity Forward Deployed Engineer - FDE Senior Manager

About the role

This is not a security consulting role, a compliance advisory position, or a pen-test engagement. A Cybersecurity Forward Deployed Engineer is a production engineer who works embedded inside a client’s enterprise—shoulder to shoulder with their security and engineering teams—to make AI systems secure, governed, and resilient in real, complex organizational environments. You own outcomes: reduced attack surface, production-safe AI deployments, measurable security posture improvement. Agentic coding is the primary method of delivery; you use Claude Code, Cursor, or GitHub Copilot as your standard operating environment to build security tooling, detection systems, threat models, and governance frameworks with AI co-authoring the code alongside you.

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 programme. The pod operates in 90-day delivery cycles, owns end-to-end outcomes across build, deploy, and optimize, and embeds directly inside the client’s technology organization.

Responsibilities

• Lead AI security architecture and threat modeling for production agentic deployments across complex multi-stakeholder client environments—LLM systems, multi-agent pipelines, RAG architectures, and MLOps infrastructure—owning the full security design from assessment through hardened deployment.
• Deliver hands-on security engineering using agentic coding tools as the primary build environment: 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.
• Own AI-specific threat surface management at programme scale: OWASP LLM Top 10 controls, prompt injection hardening, model extraction prevention, adversarial input defences, and AI supply chain security 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 multi-system integration risk across cloud platforms (AWS, Azure, or GCP).
• Lead AI governance framework implementation: EU AI Act, NIST AI RMF, and model risk management applied to live production systems, not theoretical compliance exercises.
• Shape AI reinvention security strategy for client CISO and CTO: build 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 multiple client engagements and grow the Secure AI practice.
• Lead architecture design sessions, threat modeling workshops, and code-with sessions with client engineering and security leadership teams.
• Cybersecurity domain expertise in at least one discipline (AppSec, SecOps, IAM, cloud, GRC, or offensive security).
• Proposal and SOW development, solution shaping, and client commercial engagement.
• Executive workshop facilitation and C-suite / CISO-level communication.
• Structured analytical thinking and hypothesis-driven problem decomposition.
• Team leadership: developing and coaching managers and consultants through delivery.

Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.

Requirements

• Minimum of 10 years of engineering experience in production environments with a cybersecurity discipline depth 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 a production environment—non-negotiable; theoretical familiarity does not qualify.
• Minimum 8 years of demonstrated 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).

Skills

• Proven ability to communicate security risk in business terms: can translate threat exposure into risk-adjusted investment rationale a CISO or CFO would act on.
• People lead responsibilities: experience managing, developing, and performance-managing a team of engineers; setting individual development plans and conducting career conversations.

Pay

Compensation varies by location. Annual salary ranges for this role are:

• California: $132,500 to $366,300
• Cleveland: $122,700 to $293,000
• Colorado: $132,500 to $316,400
• District of Columbia: $141,100 to $337,000
• Illinois: $122,700 to $316,400
• Maine: $112,900 to $269,600
• Maryland: $132,500 to $316,400
• Massachusetts: $132,500 to $337,000
• Minnesota: $132,500 to $316,400
• New York: $122,700 to $366,300
• New Jersey: $141,100 to $366,300
• Virginia: $122,700 to $337,000
• Washington: $141,100 to $337,000

Benefits

Accenture offers a market-competitive suite of benefits including:

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

For more details, visit U.S. Employee Benefits | Accenture.