Location: Minneapolis, MN (onsite)

Compensation

Salary: USD 87,400 - 305,000 per year

Responsibilities

Own end-to-end AI security architecture and threat modeling for production agentic deployments across large, multi-client environments, covering LLMs, multi-agent pipelines, retrieval-augmented generation, and MLOps, from initial assessment to hardened deployment.
Deliver hands-on security engineering in an agentic coding environment to build AI-powered detection, automated threat response tooling, security assessment frameworks, and governance automation using Claude Code, Cursor, or GitHub Copilot in daily work.
Manage AI-specific threat surfaces at program scale, including OWASP LLM Top 10 controls, prompt-injection hardening, model extraction prevention, adversarial input defenses, and AI supply chain security across concurrent client streams.
Architect and govern AI security controls across the enterprise stack, encompassing AI system identity and access, data-pipeline security, model-serving security, and cross-system integration risk across AWS, Azure, or GCP.
Lead the implementation of AI governance frameworks, applying EU AI Act, NIST AI RMF, and model risk management to live production environments rather than theoretical compliance tasks.
Shape security strategy for AI reinvention in collaboration with client CISOs and CTOs, developing risk-adjusted investment cases, roadmaps, and operating models that align with business outcomes.
Define and publish reusable security patterns, playbooks, and accelerators to scale across client engagements and expand the Secure AI practice.
Facilitate architecture design sessions, threat modeling workshops, and code-with sessions with client engineering and security leadership.

Requirements

Minimum 8 years of engineering experience in production settings with deep expertise in at least one cybersecurity domain (AppSec, SecOps/detection, cloud security, IAM, offensive security/pen-testing, or GRC).
At least 1 year of hands-on experience designing and deploying agentic AI solutions in production; theoretical familiarity does not qualify.
At least 6 years of end-to-end security delivery ownership in a client-embedded or production context; internal advisory or compliance-only roles do not qualify.
Six years of experience with cloud 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 using 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, and long-term disability coverage
401(k) plan
Bonus opportunities
Paid holidays
Paid time off

Accommodations

Accenture provides equal employment opportunities and offers reasonable accommodations for disabilities or religious observances during recruitment and employment. If accommodation is needed to perform essential functions or during the hiring process, please contact the toll-free number or your recruiter for assistance.

Equal Employment Opportunity

We do not discriminate on any protected basis. All hiring decisions are made regardless of age, race, creed, color, religion, sex, national origin, disability, veteran status, sexual orientation, gender identity or expression, or other protected characteristics. Details are available in Accenture's Equal Opportunity Statement.

Other Employment Information

U.S. applicants must have work authorization without current or future visa sponsorship requirements. Some roles may require travel up to varying percentages based on client needs. Applicants currently employed by a client or affiliated Accenture business may have additional eligibility considerations.

Travel

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

Cybersecurity Forward Deployed Engineer - FDE - Manager

Job Description