Llm Threat Modeling Engineer Jobs

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Cybersecurity AI Forward Deployed Engineer - FDE - Consultant

Accenture New York, NY

New York, NY

Today

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

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Job Description

Accenture is hiring a Cybersecurity Forward Deployed Engineer (FDE) consultant to embed within client enterprise teams and help secure AI systems in production. In this role, you will focus on agentic coding as the primary delivery method, partnering closely with security and engineering leadership to deliver resilient, governed AI outcomes in complex, real-world environments.

Role overview

As an FDE, you are a production engineer working shoulder to shoulder with the client’s organization to reduce attack surface and improve security posture through hardened deployments. This position is outcome-driven and operates as part of Accenture’s Reinvention Delivery Engine (RDE) Pod, aligned to a client’s business domain or AI programme.

Responsibilities

Support AI security architecture and threat modeling for production agentic deployments across complex multi-stakeholder environments, covering LLM systems, multi-agent pipelines, RAG architectures, and MLOps infrastructure, owning security design from assessment through hardened deployment
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
Manage AI-specific threat surface at programme scale, applying 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 multi-system integration risk across AWS, Azure, or GCP
Help implement AI governance frameworks for live production systems, including EU AI Act and NIST AI RMF, along with model risk management
Support AI reinvention security strategy for client CISO and CTO by 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 that scale across client engagements and grow the Secure AI practice
Contribute to architecture design sessions, threat modeling workshops, and code-with sessions with client engineering and security leadership teams

Required experience

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 production (theoretical familiarity does not qualify)
Minimum 3 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 (minimum 12 years work experience); if an Associate’s Degree, must have minimum 6 years work experience
Proven ability to communicate security risk in business terms, translating threat exposure into risk-adjusted investment rationale that a CISO or CFO can act on

Technologies

Claude Code, Cursor, GitHub Copilot
AWS, Azure, GCP
OWASP LLM Top 10
EU AI Act, NIST AI RMF

Travel

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

Compensation and location

Location: New York, NY (onsite)
Salary: USD 59,100 - 235,100 per year

Benefits

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

Within the role, agentic coding is not optional and is treated as the primary delivery method. The work is designed around production engineering embedded with client teams rather than a security consulting engagement, a compliance advisory position, or a penetration testing effort.

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