Senior AI Security Engineer Lead — Embedded, Production-Ready

Accenture

Nashville (TN)

On-site

USD 120,000 - 190,000

Full time

7 days ago

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Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

401(k) plan

Paid holidays & Paid time off

Job summary

Accenture is hiring a Cybersecurity Forward Deployed Engineer to work embedded with client security and engineering teams, delivering production‑level AI security, governance, and threat modeling capabilities. You will own outcomes like reduced attack surface and secure AI deployments, using Claude Code, Cursor, or GitHub Copilot in daily practice.

Role operates within Accenture’s Reinvention Delivery Engine, focusing on end‑to‑end security delivery, architecture, risk management, and executive

Qualifications

Bachelor's degree or equivalent work experience in a relevant field.
10+ years engineering experience in production environments with a cybersecurity discipline.
2+ years hands-on experience designing and deploying agentic AI solutions.
8+ years end-to-end security delivery ownership in a client-embedded or production environment.
8+ 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
Cybersecurity domain expertise in at least one discipline (AppSec, SecOps, IAM, cloud, GRC, or offensive security)
Proposal and SOW development, solution shaping, and client commercial engagement
Executive workshop facilitation and C-suite / CISO-level communication
Structured analytical thinking and hypothesis-driven problem decomposition
Team leadership: developing and coaching managers and consultants through delivery
Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.