Cybersecurity Forward Deployed Engineer - FDE - Manager

Accenture offers a comprehensive benefits package, including medical, dental, vision, life, and long-term disability coverage, a 401(k) plan, bonus opportunities, paid holidays, and paid time off. This onsite role in Minneapolis centers on securing, governing, and hardening AI systems in production, guiding security design and delivery for client AI deployments within a 90-day delivery pod.

Responsibilities

• Own the security architecture and threat modeling for production agentic AI deployments across complex multi-stakeholder environments, including LLMs, multi-agent pipelines, retrieval-augmented generation, and MLOps, guiding the full design from assessment to hardened deployment
• Execute practical security engineering using agentic coding tools as the primary build environment, constructing AI-powered detection systems, automated threat response capabilities, security assessment frameworks, and governance automation with Claude Code, Cursor, or GitHub Copilot
• Manage AI specific threat surface 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 cross-system integration risk across AWS, Azure, or GCP
• Lead AI governance framework implementations, applying EU AI Act, NIST AI RMF, and model risk management to live production systems
• Shape security strategy for client CISOs and CTOs, building risk-adjusted investment cases, security architecture roadmaps, and AI governance operating models aligned with business outcomes
• Define and publish reusable security patterns, playbooks, and accelerators that scale across client engagements and help grow the Secure AI practice
• Lead architecture design sessions, threat modeling workshops, and code-with sessions with client engineering and security leadership teams

Technologies

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

Requirements

• At least eight years of engineering experience in production with deep cybersecurity expertise in at least one area such as application security, SecOps/detection engineering, cloud security, IAM, offensive security/penetration testing, or governance, risk, and compliance
• Minimum one year of hands-on experience designing and deploying agentic AI solutions in production environments; theoretical knowledge alone does not qualify
• Six or more years 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 platform security fundamentals across AWS, Azure, or GCP, including 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, at least six years of work experience is required

Professional Skills

• Ability to translate security risk into business terms and present risk-adjusted investment rationales
• Experience managing, developing, and performance-managing a team of engineers, including setting development plans and conducting career conversations

Travel

Travel may be required; the amount can vary from 0 to 100 percent depending on business needs and client requirements.