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Cybersecurity Forward Deployed Engineer - FDE Senior Manager

Accenture · Albany, New York Metropolitan Area · 2 wk ago
Engineering$133k–$366k/yrFull-time

About the role

Cybersecurity Forward Deployed Engineers (FDEs) operate as part of Accenture’s Reinvention Delivery Engine (RDE) Pod. This Pod is a small, persistent, outcome-oriented team aligned to a client’s business domain or AI program. The Pod operates in 90-day delivery cycles, owning end-to-end outcomes across build, deploy, and optimize, and embeds directly inside the client’s technology organization.

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

Requirements

  • 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 / penetration testing, or GRC

  • Minimum 2 years 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

Qualifications

  • Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience)

Skills

  • Proven ability to communicate security risk in business terms: can translate threat exposure into risk-adjusted investment rationale a CISO or CFO would act on

  • People lead responsibilities: experience managing, developing, and performance-managing a team of engineers; setting individual development plans and conducting career conversations

Pay

Annual Salary Range: $132,500 to $366,300

Schedule

Full-time

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