SVP AI Enterprise Architect
About The Position
The SVP, AI Architect will serve as a strategic member of the Enterprise Architecture organization, providing expert guidance, thought leadership, and hands-on support across all areas of generative AI and machine learning within the enterprise. This role is responsible for shaping and influencing the organization’s AI strategy, ensuring that innovation is pursued with intention, security, and appropriate governance. In this role, the AI Architect will drive controlled and sustainable AI adoption, enabling meaningful efficiency gains through intelligent automation, process optimization, and the integration of advanced AI capabilities into enterprise solutions. Success requires a deep and ongoing awareness of emerging AI technologies, evolving industry best practices, and the rapidly shifting landscape of generative AI. The ideal candidate understands how AI can augment and streamline the developer experience, improve delivery velocity, and enhance solution quality. Equally important is the ability to bridge business objectives with technical architectures—translating complex concepts into actionable strategies and ensuring that AI solutions align with enterprise priorities, value drivers, and risk management frameworks.
Requirements
- Advanced degree (Master’s or PhD) in AI, Data Science, Computer Science, or related field.
- Professional certifications in AI, machine learning, cloud architecture, or enterprise architecture.
- Experience with compliance and regulatory aspects of AI in financial services.
- Proficiency in programming languages such as Python and experience with AI/ML frameworks.
- This role is primarily not a hands-on role, though building PoC and demo applications should be within their skillset so the chosen candidate should have strong programming skills, likely in Python or any OOP language (Java, C/C++, C#/.NET, Rust, Go, etc.).
- Model training or fine tuning experience
- Holds an Advanced cloud certification in Azure
- Experience with LangChain, TensorFlow, PyTorch, or Databricks SDKs for ML
Nice To Haves
- Deep experience with generative AI, machine learning, and enterprise‑grade AI/ML systems in regulated industries.
- Strong enterprise architecture background and ability to align AI solutions with business strategy.
- Expertise in AI governance, regulatory frameworks, and implementing compliant risk controls.
- Proven experience scaling AI adoption across cross‑functional teams.
- Familiarity with AI architecture frameworks, MLOps best practices, and CI/CD for agentic applications.
- Mastery of Azure AI Foundry and working knowledge of AWS generative AI tools.
- Strong understanding of RAG applications and advanced prompt engineering techniques.
- Knowledge of tradeoffs across leading model providers and alignment to enterprise constraints.
- Experience tuning vector databases such as Postgres, Databricks, and Azure Search.
- Ability to define measurable AI ROI and differentiate AI vs automation use cases.
Responsibilities
- Provide input, guidance, and expertise on generative AI and machine learning within the enterprise
- Drive controlled growth in AI initiatives and deliver efficiency gains through automation and AI adoption
- Stay abreast of the latest AI developments and technologies
- Advise on how AI can enhance the developer experience and consult with application development teams
- Bridge the gap between business and technology by aligning technical solutions with business needs
- Drive AI governance through Architecture Review Boards
Benefits
- retirement benefits (401k and pension)
- health and welfare benefits (medical, dental, vision, spending accounts and disability)
- paid time off
- parental and caregiver leave
- life & accident insurance
- other voluntary and well-being benefits
- discretionary bonus program that may include an equity component
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What This Job Offers
Job Type
Full-time
Career Level
Senior
