Cybersecurity AI Forward Deployed Engineer

Cybersecurity Jobs; Kirkland (WA); On-site; USD 59,000 - 235,000; Full time

Benefits offered by this job

Medical, dental, vision, life, and LTD

401(k) plan

Bonus opportunities

Paid holidays

Paid time off

Job summary

Accenture Security is seeking a Cybersecurity AI Forward Deployed Engineer to embed inside client enterprises in Kirkland, WA (onsite). You will help secure and govern AI systems in production by applying security architecture and threat modeling to real agentic deployments.

You will work across complex, multi‑stakeholder environments addressing security for LLM systems, multi‑agent pipelines, RAG architectures, and MLOps infrastructure with hands‑on security engineering using agentic coding

Qualifications

• Minimum 3 years of engineering experience in production environments with depth in at least one area: AppSec, SecOps/detection engineering, cloud security, IAM, offensive security or GRC.
• Minimum 1 year hands‑on experience designing and deploying agentic AI solutions in production.
• Minimum 3 years working with cloud platform security fundamentals across AWS, Azure, or GCP: IAM, network security, secrets management, and AI service security configurations.
• Bachelor's degree or equivalent work experience (min 12 years); if Associate’s Degree, min 6 years work experience.
• Proven ability to communicate security risk in business terms and translate threat exposure into risk‑adjusted investment rationale.

Responsibilities

• Support AI security architecture and threat modeling for production agentic deployments, owning security design from assessment through hardened deployment.
• Deliver hands‑on security engineering using agentic coding tools to build AI‑powered detection systems, automated threat response tooling, security assessment frameworks, and governance automation.
• Manage AI‑specific threat surface at program scale, including OWASP LLM Top 10 controls, prompt injection hardening, model extraction prevention, adversarial input defenses, and AI supply chain security.
• Architect and govern AI security controls across the enterprise stack, including identity and access for AI systems, data pipeline security, model serving security, and integration risk across AWS, Azure, or GCP.
• Assist with implementing AI governance frameworks such as the EU AI Act and NIST AI RMF, applied to live production systems not theoretical compliance work.
• Support AI reinvention security strategy for client leadership by creating risk‑adjusted investment cases, roadmaps, and governance operating models aligned to business outcomes.
• Define and publish reusable security patterns, playbooks, and accelerators that scale across client engagements to grow the Secure AI practice.
• Contribute to architecture design sessions, threat modeling workshops, and code‑with sessions with client engineering and security leadership.

Skills

AppSec

SecOps

Cloud security

IAM

Penetration testing

GRC

Education

Bachelor's degree or equivalent

Tools

Claude Code

Cursor

GitHub Copilot

OWASP LLM Top 10

AWS

Azure

GCP

Job description

Accenture Security is hiring a Cybersecurity AI Forward Deployed Engineer to embed inside client enterprises in Kirkland, WA (onsite). In this role, you will help make AI systems secure, governed, and resilient in production by applying security architecture and threat modeling to real agentic deployments.

What you can expect

You will work across complex, multi-stakeholder environments, addressing security for LLM systems, multi-agent pipelines, RAG architectures, and MLOps infrastructure. The work is hands‑on and delivered using agentic coding tools to build detection and governance capabilities that support live production systems.

Responsibilities

• Support AI security architecture and threat modeling for production agentic deployments, owning security design from assessment through hardened deployment across complex client environments.
• Deliver hands‑on security engineering using agentic coding tools to build AI‑powered detection systems, automated threat response tooling, security assessment frameworks, and governance automation.
• Manage AI‑specific threat surface 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 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 integration risk across AWS, Azure, or GCP.
• Assist with implementing AI governance frameworks such as the EU AI Act and NIST AI RMF, applied to live production systems rather than theoretical compliance work.
• Support AI reinvention security strategy for client leadership by creating 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 to grow the Secure AI practice.
• Contribute to architecture design sessions, threat modeling workshops, and code‑with sessions with client engineering and security leadership teams.

Requirements

• Minimum 3 years of engineering experience in production environments with 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 (theoretical familiarity does not qualify).
• Minimum 3 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 an Associate’s Degree, minimum 6 years work experience.
• Proven ability to communicate security risk in business terms, translating threat exposure into risk‑adjusted investment rationale a CISO or CFO would act on.

Technologies

• Claude Code, Cursor, GitHub Copilot
• OWASP LLM Top 10
• EU AI Act, NIST AI RMF
• AWS, Azure, GCP
• LLM systems, multi‑agent pipelines, RAG architectures, MLOps infrastructure

Benefits

• Medical, dental, vision, life, and long‑term disability coverage
• 401(k) plan
• Bonus opportunities
• Paid holidays
• Paid time off

Travel

Travel may be required. The amount of travel will vary from 0 to 100% depending on business need and client requirements.

Salary range: USD 59,100 - 235,100 per year.