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Digital - AI Security Architect - Senior Manager

Key Facts

Remote From: 
Full time
Senior (5-10 years)
English

Other Skills

  • Consulting
  • Communication
  • Teamwork
  • Consulting
  • Problem Solving

Roles & Responsibilities

  • 8+ years of experience in software engineering, cybersecurity, or AI/ML, including architecture roles
  • Proven experience delivering secure, production-grade AI or generative AI solutions
  • Deep knowledge of LLM-based and agentic AI architectures
  • Strong understanding of cloud platforms (Azure, AWS, or GCP) and cloud security capabilities

Requirements:

  • Design and implement secure AI and generative AI architectures across data, model development, deployment, and inference
  • Embed security controls into LLM, RAG, and agentic AI systems
  • Guide architectural decisions on data pipelines, model orchestration, APIs, and observability
  • Design AI auditability and observability solutions to support governance, monitoring, and incident response

Job description

Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation and navigate constant change. Through a combination of strategy, expertise and creativity, we help clients accelerate operational, digital and cultural transformation, enabling the change they need to own their future. 

Join our team as the expert you are now and create your future.

Huron is seeking a senior-level AI Security Architect to help clients design, secure, and scale enterprise AI and generative AI solutions. This role combines hands-on technical architecture with client-facing advisory, focusing on security, risk management, and governance across the AI lifecycle.
You will serve as a trusted advisor to clients, helping them deploy AI responsibly while addressing emerging security threats and regulatory requirements. This is a senior individual contributor role with no direct reports, requiring both deep technical expertise and the ability to guide client decisions.

Key Responsibilities

AI Architecture & Delivery

  • Design and implement secure AI and generative AI architectures across data, model development, deployment, and inference
  • Embed security controls into LLM, RAG, and agentic AI systems
  • Guide architectural decisions on data pipelines, model orchestration, APIs, and observability
  • Design AI auditability and observability solutions to support governance, monitoring, and incident response

Security, Risk & Governance

  • Identify and mitigate AI-specific risks (e.g., prompt injection, data leakage, model poisoning, adversarial attacks)
  • Conduct threat modeling, architecture risk assessments, and AI security testing (e.g., red teaming) for AI systems
  • Assess AI supply chain risk, including model provenance, third-party models, and training data lineage
  • Define and recommend AI security standards, policies, and MLSecOps practices aligned to regulatory and enterprise risk frameworks
  • Translate technical risks into executive-ready, business-aligned guidance

Client Advisory & Practice Contribution

  • Act as a trusted advisor to client leaders on secure and responsible AI adoption
  • Contribute to proposals, workshops, and AI security solution shaping
  • Develop reusable assets, reference architectures, and thought leadership

Required Qualifications

  • 8+ years of experience in software engineering, cybersecurity, or AI/ML, including architecture roles
  • Proven experience delivering secure, production-grade AI or generative AI solutions
  • Deep knowledge of LLM-based and agentic AI architectures
  • Strong understanding of cloud platforms (Azure, AWS, or GCP) and cloud security capabilities
  • Expertise in identity and access management (IAM), data protection, API security, and risk assessment
  • Ability to assess and communicate technical risks in a business context
  • Experience working in client-facing environments with both technical and business stakeholders

Preferred Experience

  • Deep expertise in AI security risks and controls, including OWASP Top 10 for LLMs, NIST AI RMF, or similar
  • Experience securing agentic AI systems and autonomous workflows
  • AI governance, policy development, and enterprise guardrails
  • Experience with AI security testing, including adversarial testing approaches
  • Implementation of secure AI lifecycle / MLSecOps practices
  • Experience in regulated environments (e.g., HIPAA, SOX, FedRAMP, NIST 800-53)
  • Relevant certifications (e.g., CISSP, CCSP, cloud security certifications)

Why Huron

At Huron, we partner with clients to innovate responsibly—designing AI solutions that are secure, compliant, and built to scale. Our teams combine deep technical expertise with a practical, results-oriented approach to help organizations realize long-term value from AI.

The estimated base salary for this job is $175,000 - $195,000. The range represents a good faith estimate of the range that Huron reasonably expects to pay for this job at the time of the job posting. The actual salary paid to an individual will vary based on multiple factors, including but not limited to specific skills or certifications, years of experience, market changes, and required travel. This job is also eligible to participate in Huron’s annual incentive compensation program, which reflects Huron’s pay for performance philosophy. Inclusive of annual incentive compensation opportunity, the total estimated compensation range for this job is $210,000 - $234,000. The job is also eligible to participate in Huron’s benefit plans which include medical, dental and vision coverage and other wellness programs. The salary range information provided is in accordance with applicable state and local laws regarding salary transparency that are currently in effect and may be implemented in the future.

Position Level

Senior Manager

Country

United States of America

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