AI Architect

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🏄 California – Remote

🏄 California – Remote

⏰ Full Time

🟠 Senior

🔴 Lead

🤖 AI Engineer

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ISC2

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 1989

🔒 Cybersecurity

📚 Education

☁️ SaaS

Cybersecurity • Education • SaaS

ISC2 is a leading organization dedicated to advancing cybersecurity education and certification. They provide various programs for individuals at different stages of their cybersecurity careers, including certification exams, training resources, and leadership development opportunities. ISC2 also advocates for members and promotes diversity within the cybersecurity field by empowering professionals and communities.

📋 Description

• Define and document enterprise AI use cases, business value drivers, and target delivery models that align with organizational goals and objectives. • Develop and maintain current-state and target-state AI architecture across the enterprise, including platforms, data flows, integration patterns, security controls, and governance requirements. • Lead build-versus-buy evaluations for AI platforms and services, and provide appropriate recommendations. • Establish reusable AI architecture patterns, reference models, and implementation standards to support consistent delivery. • Guide proof-of-concept and pilot strategies to validate solution feasibility, technical design, business value, and operational readiness before broader adoption. • Drive scalable AI operations by embedding monitoring, telemetry, observability, governance, and change management practices across the AI lifecycle. • Partner with architecture, engineering, data, security, product, and business stakeholders to translate requirements into secure, reliable, and governed AI solutions. • Define key deliverables for the function, including AI architecture models, proof-of-concept strategies, and delivery patterns that accelerate enterprise adoption. • Perform miscellaneous duties, as required.

🎯 Requirements

• Deep knowledge of AI/ML concepts and patterns, including machine learning, generative AI, large language models (LLMs), prompt design, retrieval-augmented generation (RAG), model evaluation, and responsible AI practices. • Hands-on proficiency with Python and familiarity with common AI/ML frameworks and tooling such as PyTorch, TensorFlow, scikit-learn, LangChain or Semantic Kernel, APIs, and vector databases. • Demonstrated expertise in MLOps / LLMOps practices, including CI/CD, model deployment, observability, telemetry, drift and performance monitoring, cost optimization, and lifecycle management. • Strong understanding of AI security, privacy, governance, and compliance requirements, including access controls, data protection, auditability, risk management, bias mitigation, and human-in-the-loop controls. • Relevant cloud, architecture, or AI certifications are preferred (for example, Azure AI Engineer, AWS Machine Learning, Google Professional Machine Learning Engineer, or equivalent architecture certifications). • Proven ability to conduct build-versus-buy assessments, evaluate vendors and platforms, define reference architectures, and establish reusable design patterns and standards. • Excellent collaboration and communication skills, with the ability to translate business priorities into technical roadmaps, solution designs, proof-of-concept strategies, and executive-ready recommendations. • Strong analytical and management capabilities, including facilitation of cross-functional teams, change management, and mentoring delivery teams on AI architecture best practices.

🏖️ Benefits

• Equal Employment Opportunity Statement All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic as protected by applicable law. Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process.