Sr AI Architect, Application Security

United StatesRemoteFull-timesenior

ArchitectConstruction & Real Estate

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Requirements Summary

Professional Experience: A high school diploma with at least seven years of relevant experience, a bachelor's degree with at least three years of experience,

Technical Tools

ArchitectConstruction & Real Estate

We are looking for a senior, hands-on AI Architect to shape the future of secure AI adoption and agentic technology within an established cybersecurity practice. In this strategic role, you will design, build, and secure advanced AI-powered systems that enhance security consulting and delivery capabilities. You will also advise enterprise clients on AI strategy, governance, architecture, and risk management, helping them move from experimentation to secure production environments. Working closely with engineering teams, executive stakeholders, and leading AI technology providers, you will influence technical direction and innovation. This is an opportunity to combine deep technical expertise, client-facing leadership, and mentoring in a fast-evolving, AI-driven environment.

AI Architecture and Platform Development: Define the technical architecture, roadmap, and secure design of an agentic delivery platform, including AI agents, prompts, skills, MCP servers, integrations, and orchestration workflows that support application security assessments, threat modeling, code reviews, and architecture reviews.
Agentic Systems Engineering: Design, build, and maintain AI-powered capabilities, including agent workflows, retrieval strategies, context management, tool integrations, and evaluation frameworks to ensure accuracy, reliability, and consistency.
AI Security and Governance: Apply secure-by-design principles across internal AI systems by conducting threat models, enforcing least-privilege access, establishing autonomy boundaries, protecting client data, and implementing security controls aligned with OWASP, NIST AI Risk Management Framework, and MITRE ATLAS.
Client Advisory and Architecture: Serve as a forward-deployed security architect, collaborating with enterprise engineering, platform, data science, and security teams to assess and strengthen application and AI architectures.
AI Strategy and Transformation: Advise clients on AI adoption, governance, responsible AI practices, threat modeling, secure reference architectures, and implementation roadmaps that support the transition from AI pilots to enterprise-scale production.
Training and Enablement: Develop and deliver technical training, workshops, and enablement programs covering secure AI development, agentic security, prompt injection, AI governance, and AI-assisted development tools.
Technology Partnerships: Act as a senior technical liaison with AI labs and model providers, evaluating new capabilities, participating in technical partner programs, and translating emerging developments into practical solutions and services.
Technical Leadership and Mentorship: Establish architectural standards, review technical designs, mentor consultants, and collaborate with practice leadership, sales, and solution architects to develop service offerings and support client engagements.
Research and Industry Engagement: Contribute to AI and application security research through conference presentations, technical articles, whitepapers, webinars, and open-source initiatives while continuously exploring emerging technologies and best practices.

Requirements

~3 min read

Professional Experience: A high school diploma with at least seven years of relevant experience, a bachelor's degree with at least three years of experience, or a master's degree in a relevant discipline.
Security and Architecture Background: At least three years of experience in security architecture, application security, software engineering, or platform engineering, with demonstrated ownership of system-level architectural decisions.
Client-Facing Experience: At least one year of experience in enterprise consulting or technical advisory roles, with the ability to work directly with clients and senior stakeholders.
AI and Agentic Engineering Expertise: Demonstrated hands-on experience designing and building AI agents and agentic systems, including orchestration frameworks, prompt engineering, tool and function calling, MCP servers, retrieval-augmented generation, context management, and evaluation frameworks.
LLM Development Skills: Strong development and scripting capabilities in Python, TypeScript, JavaScript, or comparable languages, with practical experience using LLM APIs and SDKs such as OpenAI, Anthropic, Amazon Bedrock, or Azure OpenAI.
AI Security Knowledge: Ability to securely architect AI-native and agentic systems, with practical knowledge of the OWASP Top 10 for LLM Applications and the OWASP Top 10 for Agentic Applications.
Application Security Expertise: Working knowledge of application security assessments, threat modeling, secure code reviews, architecture reviews, and Secure SDLC practices.
Technical Communication: Excellent ability to explain complex architecture decisions and AI strategies to engineering teams, executives, and external technology partners.
Leadership and Collaboration: Strong interpersonal skills, strategic thinking, and the ability to lead through influence, mentor technical professionals, and collaborate across multidisciplinary teams.
Adaptability and Innovation: Genuine enthusiasm for emerging technologies and a demonstrated willingness to use AI-enabled tools to improve productivity and business outcomes.

Preferred qualifications:

More than seven years of combined IT and information security experience, including application security or software architecture responsibilities.
Experience delivering enterprise AI strategy, AI governance, or responsible AI advisory engagements, with familiarity with frameworks such as NIST AI Risk Management Framework, ISO/IEC 42001, or the EU AI Act.
Experience working as a forward-deployed, embedded, or resident architect alongside client engineering teams.
Background developing and delivering technical training, workshops, and enablement programs for technical and executive audiences.
Experience participating in AI vendor technical partnerships, design-partner initiatives, or subject-matter-expert programs.
Internal operational experience in DevSecOps, platform engineering, MLOps, or LLMOps.
Active involvement in the information security community through conference speaking, technical publications, podcasts, or open-source contributions.
Relevant certifications in AI architecture, generative AI, application security, or enterprise security, such as Anthropic Claude Certified Architect, AWS, Microsoft, Google Cloud, NVIDIA, OSWE, GWAPT, CISSP, or CCSP. Certification is advantageous but not mandatory, and professional development support is available.