AI Security Engineer: Embedded & Production-Ready

Accenture; Denver (CO); Hybrid; USD 94,000 - 273,000; Full time

Benefits offered by this job

Medical insurance

Dental and vision

401(k)

Job summary

Accenture’s Cybersecurity Forward Deployed Engineers embed with client security teams to secure AI systems in real-world environments, delivering production‑ready security controls and governance. You own outcomes—reducing attack surfaces, enabling resilient AI deployments, and improving security posture through hands‑on engineering and AI tooling.

You operate within Accenture’s Reinvention Delivery Engine, collaborating across build, deploy, and optimize cycles to embed security across client

Qualifications

• Minimum 8 years of production engineering with a cybersecurity discipline depth in at least one area.
• Minimum 1 year hands-on experience designing and deploying agentic AI solutions in a production environment—non‑negotiable; theoretical familiarity does not qualify
• Minimum 6 years of demonstrated end-to-end security delivery ownership experience in a client-embedded or production environment
• Minimum 6 years working with Cloud platform security fundamentals across at least one provider (AWS, Azure, or GCP)

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

Skills

Security architecture

Threat modeling

Cloud security

GRC

Agentic coding

Education

Bachelor's degree or equivalent

Tools

Claude Code

Cursor

GitHub Copilot

Job description

Accenture’s Cybersecurity Forward Deployed Engineers embed with client security teams to secure AI systems in real-world environments, delivering production‑ready security controls and governance. You own outcomes—reducing attack surfaces, enabling resilient AI deployments, and improving security posture through hands‑on engineering and AI tooling.

You operate within Accenture’s Reinvention Delivery Engine, collaborating across build, deploy, and optimize cycles to embed security across client