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Forward Deployed Ai Cybersecurity Jobs

2 jobs found

Today

Cybersecurity AI Forward Deployed Engineer - FDE - Manager

Logic Austin, TX

Austin, TX

Today

$87k - $316k/yr Full time Manager Agentic Ai Security Ai Security

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Job Description

The Cybersecurity AI Forward Deployed Engineer Manager role is embedded in client environments to help secure AI systems in production. The position focuses on hands-on security engineering, including threat modeling, governance implementation, and measurable improvements to security posture across complex AI programs.

Key Responsibilities

Lead AI security architecture and threat modeling for production agentic deployments across complex, multi-stakeholder client environments, owning the security design from assessment through hardened deployment for LLM systems, multi-agent pipelines, RAG architectures, and MLOps infrastructure.
Perform hands-on security engineering using agentic coding tools as the primary build environment, including building AI-powered detection systems, automated threat response tooling, security assessment frameworks, and governance automation with Claude Code, Cursor, or GitHub Copilot.
Own AI-specific threat surface management at programme scale using 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, covering identity and access for AI systems, data pipeline security, model serving security, and integration risk across AWS, Azure, or GCP.
Lead implementation of an AI governance framework for production systems, including EU AI Act, NIST AI RMF, and model risk management applied to live environments.
Shape an AI reinvention security strategy in alignment with client CISO and CTO priorities by developing 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.
Run architecture design sessions, threat modeling workshops, and code-with sessions with client engineering and security leadership teams.

Required Qualifications

Minimum 8 years of engineering experience in production environments with cybersecurity discipline depth in at least one area: AppSec, SecOps and/or detection engineering, cloud security, IAM, offensive security and/or penetration testing, or GRC.
Minimum 1 year of hands-on experience designing and deploying agentic AI solutions in a production environment (the role requires practical delivery; theoretical familiarity is not sufficient).
Minimum 6 years demonstrating end-to-end security delivery ownership in a client-embedded or production environment; internal advisory or compliance-only roles do not qualify.
Minimum 6 years working with cloud platform security fundamentals across at least one provider: AWS, Azure, or GCP, including IAM, network security, secrets management, and AI service security configurations.
Bachelor’s degree or equivalent with a minimum of 12 years work experience. If an Associate’s Degree is held, minimum 6 years work experience is required.
Proven ability to communicate security risk in business terms, translating threat exposure into risk-adjusted investment rationale for a CISO or CFO.
People leadership experience managing, developing, and performance-managing a team of engineers, including setting individual development plans and conducting career conversations.

Technologies and Frameworks

Agentic coding tools: Claude Code, Cursor, GitHub Copilot
Security and governance: OWASP LLM Top 10, EU AI Act, NIST AI RMF
Cloud platforms: AWS, Azure, GCP
AI delivery contexts: LLM systems, multi-agent pipelines, RAG architectures, MLOps infrastructure

Compensation and Location

Location: Austin, TX (onsite)

Salary range: USD 87,400 - 316,300 per year

Annual salary range varies by state as follows:

California: $94,400 to $316,300
Colorado: $94,400 to $273,200
Connecticut: $94,400 to $273,200
District of Columbia: $100,500 to $291,000
Illinois: $87,400 to $273,200
Maine: $80,400 to $232,800
Maryland: $94,400 to $273,200
Massachusetts: $94,400 to $291,000
Minnesota: $94,400 to $273,200
New York: $87,400 to $316,300
New Jersey: $100,500 to $316,300
Ohio: $87,400 to $253,000
Virginia: $87,400 to $291,000
Washington: $100,500 to $291,000

Benefits

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

Travel Requirements

Travel may be required for this role, ranging from 0 to 100% depending on business need and client requirements.

Accommodation and Equal Employment Opportunity

Accenture is committed to providing equal employment opportunities, including reasonable accommodations when needed for persons with disabilities or religious observances.
All employment decisions are made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status, or any other basis protected by federal, state, or local law.

Additional Employment Statements

Applicants for employment in the US must have work authorization that does not require sponsorship of a visa for employment authorization in the United States now or in the future.
Candidates currently employed by a client of Accenture or an affiliated Accenture business may not be eligible for consideration.
Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process.

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Today

Cybersecurity AI Forward Deployed Engineer

Accenture Kirkland, WA

Kirkland, WA

Today

$59k - $235k/yr Full time Adversarial Ai Security Agentic Ai Security Ai Security

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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.

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Forward Deployed Ai Cybersecurity Jobs

Cybersecurity AI Forward Deployed Engineer - FDE - Manager

Cybersecurity AI Forward Deployed Engineer

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