AI Security Forward-Deployed Engineer — Senior Leader

Accenture; Kirkland (WA); On-site; USD 141,000 - 337,000; Full time

Benefits offered by this job

Medical coverage

401(k) plan

Bonus opportunities

Paid time off

Paid holidays

Job summary

Accenture Security is seeking a production AI security engineer to own end-to-end security for embedded client AI deployments. You will lead threat modeling, design secure AI architectures, and build tooling for detection, governance, and risk management using Claude Code, Cursor, and GitHub Copilot.

This role requires deep expertise across AppSec, SecOps, IAM, and cloud security within enterprise environments.

Qualifications

• 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 / GRC
• Minimum 2 year 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)

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

Skills

AI security architecture

Threat modeling

Security delivery ownership

Cloud security fundamentals

IAM security

Education

Bachelor's degree or equivalent

Tools

Claude Code

Cursor

GitHub Copilot

Job description

Accenture Security is seeking a production AI security engineer to own end-to-end security for embedded client AI deployments. You will lead threat modeling, design secure AI architectures, and build tooling for detection, governance, and risk management using Claude Code, Cursor, and GitHub Copilot.

This role requires deep expertise across AppSec, SecOps, IAM, and cloud security within enterprise environments.