
at Accenture
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**Role**: Cybersecurity Forward Deployed Engineer - FDE - Manager **Responsibilities**: - Lead AI security architecture and threat modeling for agentic deployments, owning full security design for complex environments. - Deliver hands-on security engineering using agentic coding tools like Claude Code or GitHub Copilot. - Manage AI threat surface, implement AI governance frameworks, and shape security strategy for clients. **Required Skills & Experience**: - Proven experience as a cybersecurity professional, with a focus on AI and production use cases. - Strong background in AI security, governance, and threat management. - Proficiency in agentic coding tools such as Claude Code, Cursor, or GitHub Copilot. - Ability to work in embedded client environments and manage complex projects. - Understanding of cloud platforms (AWS, Azure, GCP), security compliance (EU AI Act, NIST AI RMF), and AI-specific risks.
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Full Job Description
We Are
Accenture Security helps organizations prepare, protect, detect, respond, and recover along with all points of the security lifecycle. Cybersecurity challenges are different for every business in every industry. Leveraging our global resources and advanced technologies, we create integrated, turnkey solutions tailored to our client's needs across their entire value chain. Whether were defending against known cyberattacks, detecting and responding to the unknown, or running an entire security operations center, we will help companies build cyber resilience to grow with confidence. Our team of the security sectors brightest people uses the coolest tech to out-hack the hackers and help clients build resilience from within. We blend risk strategy, digital identity, cyber defense, application security, and managed service solutions to rethink the entire security lifecycle.
Do you have the deep functional and technical experience to help implement security solutions that align with our clients business objectives? Do you have the expertise to design and deliver solutions for establishing system user's credentials, and processes for applying those credentials to access enterprise systems and applications?
You Are
This is not a security consulting role. It is not a compliance advisory position. It is not a pen test engagement. A Cybersecurity Forward Deployed Engineer is a production engineer who works embedded inside a clients enterpriseshoulder to shoulder with their security and engineering teamsto make AI systems secure, governed, and resilient in real, complex organizational environments. You own outcomes: reduced attack surface, production-safe AI deployments, measurable security posture improvement.
Agentic coding is not a supporting skill for this roleit is the primary method of delivery. You use Claude Code, Cursor, or GitHub Copilot as your standard operating environment. You build security tooling, detection systems, threat models, and governance frameworks with AI co-authoring the code alongside you. Engineers who treat AI tools as optional accelerators are not the profile. Engineers who cannot deliver without them are.
The Work
Cybersecurity FDEs operate as part of Accentures Reinvention Delivery Engine (RDE) Pod: a small, persistent, outcome-oriented team aligned to a clients business domain or AI program. The pod operates in 90-day delivery cycles, owns end-to-end outcomes across build, deploy, and optimize, and embeds directly inside the clients technology organization.
Key Responsibilities
Lead AI security architecture and threat modeling for production agentic deployments across complex multi-stakeholder client environmentsLLM systems, multi-agent pipelines, RAG architectures, and MLOps infrastructureowning 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
Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.




