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Job Description

Accenture is seeking a Cybersecurity Forward Deployed Engineer to join the onsite team in New York, embedded inside a client environment to secure AI systems, govern them, and ensure resilience. The role focuses on delivering tangible security outcomes, including a reduced attack surface and production‑ready AI deployments, through close collaboration with security and engineering teams. This engagement sits within Accenture's Reinvention Delivery Engine, a pod‑based, outcome‑driven model that works in 90‑day cycles aligned to a client’s AI program.

Responsibilities

  • Contribute to AI security architecture and threat modeling for production deployments across complex, multi‑stakeholder environments, including LLM systems, multi‑agent pipelines, RAG architectures, and MLOps infrastructure, owning the security design from assessment to hardened deployment.
  • Provide hands‑on security engineering using agentic coding tools as the primary build environment; develop AI‑powered detection systems, automated threat response tooling, security assessment frameworks, and governance automation using Claude Code, Cursor, or GitHub Copilot in daily practice.
  • Oversee AI specific threat surface management at program scale, addressing OWASP LLM Top 10 controls, prompt injection hardening, model extraction prevention, adversarial input defenses, and AI supply chain security across concurrent client workstreams.
  • Design and govern AI security controls across the enterprise stack, including identity and access management for AI systems, data pipeline security, model serving security, and cross‑system integration risk across cloud platforms (AWS, Azure, or GCP).
  • Assist with AI governance framework implementation, applying EU AI Act, NIST AI RMF, and model risk management to live production systems rather than theoretical exercises.
  • Shape 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 business outcomes.
  • Define and publish reusable security patterns, playbooks, and accelerators to scale across multiple client engagements and grow the Secure AI practice.
  • Participate in architecture design sessions, threat modeling workshops, and code‑with sessions with client engineering and security leadership teams.

Requirements

  • Minimum of 3 years of engineering experience in production environments with cybersecurity depth in at least one area such as 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 of experience 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 12 years of combined education and work experience. If holding 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

The Work

Cybersecurity FDEs operate as part of Accenture’s Reinvention Delivery Engine Pod, a small, persistent, outcome‑oriented team aligned to a client’s business domain or AI program. The pod works in 90‑day delivery cycles, owns end‑to‑end outcomes across build, deploy, and optimize, and embeds directly inside the client’s technology organization.

Here's What You Need

  • At least 3 years of engineering experience in production with a deep cybersecurity specialty in one area such as AppSec, SecOps/detection engineering, cloud security, IAM, offensive security/penetration testing, or GRC.
  • At least 1 year of practical, hands‑on experience designing and deploying agentic AI solutions in production.
  • Around 3 years of work 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 with a minimum of 12 years of combined education and work experience; Associate’s Degree requires a minimum of 6 years of work experience.

Professional Skills Requirements

  • Ability to communicate security risk in business terms, translating threat exposure into risk‑adjusted investment rationale that a CISO or CFO would act on.

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