Accenture seeks an accomplished Cybersecurity Forward Deployed Engineer to embed with client teams in Des Moines, IA, focusing on secure AI deployments and governance. The role centers on designing, securing, and governing AI systems through agentic coding, taking ownership of production deployments, threat modeling, and tooling within complex multi-stakeholder environments.
Below is a structured outline of responsibilities, requirements, and related details for this role.
Responsibilities
- Lead AI security architecture and threat modeling for production agentic deployments across multi-stakeholder client environments, including LLM systems, multi-agent pipelines, RAG architectures, and MLOps infrastructure, owning the full security design from assessment through hardened deployment.
- Provide hands-on security engineering using agentic coding tools as the primary build environment, building 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, 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 risk across cloud platforms (AWS, Azure, or GCP).
- Lead AI governance framework implementation, applying EU AI Act, NIST AI RMF, and model risk management to live production systems.
- Shape AI reinvention security strategy for client CISO and CTO, building 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 to scale across 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.
Requirements
- Minimum of eight years of engineering experience in production environments with deep cybersecurity expertise in at least one area: AppSec, SecOps / detection engineering, cloud security, IAM, offensive security / penetration testing, or GRC.
- At least one year of hands-on experience designing and deploying agentic AI solutions in production; theoretical familiarity does not qualify.
- Minimum six years of demonstrated 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, a minimum of six years of work experience is required.
Technologies
- Claude Code, Cursor, GitHub Copilot, AWS, Azure, GCP
Benefits
- Medical, dental, vision, life, and long-term disability coverage
- 401(k) plan
- Bonus opportunities
- Paid holidays
- Paid time off
Professional Skills Requirements
- Ability to translate security risk into business terms, converting threat exposure into risk-adjusted investment rationale that 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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