Cybersecurity Forward Deployed Engineer - FDE - Manager

Key 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

Here's what you need

• Minimum of 8 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 1 year of hands-on experience designing and deploying agentic AI solutions in a production environment—non-negotiable; theoretical familiarity does not qualify
• Minimum 6 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 6 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

Professional Skills Requirements

• 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 at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience.