Enterprise Architect - AI/ML - New York

Photon•New York, NY

5d•$62,000 - $217,000•Onsite

About The Position

We are looking for an experienced Enterprise Architect – AI/ML to define and lead the enterprise-wide architecture strategy for Artificial Intelligence, Machine Learning, Generative AI, and emerging AI technologies. The role will be responsible for establishing AI/ML architecture principles, technology strategy, reference architectures, governance frameworks, and adoption roadmaps across the organization. The architect will partner with business leaders, technology leadership, data teams, engineering teams, security, and product organizations to identify AI opportunities and transform them into scalable, secure, governed, and business-aligned solutions. The ideal candidate combines strong enterprise architecture expertise with deep knowledge of AI/ML, Generative AI, cloud, data platforms, application architecture, security, and AI governance.

Requirements

Strong enterprise architecture expertise
Deep knowledge of AI/ML
Deep knowledge of Generative AI
Deep knowledge of cloud platforms
Deep knowledge of data platforms
Deep knowledge of application architecture
Deep knowledge of security
Deep knowledge of AI governance

Responsibilities

Define the enterprise AI/ML architecture strategy and technology roadmap aligned with business objectives.
Establish enterprise-wide AI/ML architecture principles, standards, patterns, and reference architectures.
Define target-state architecture for AI/ML platforms, Generative AI, LLM applications, RAG solutions, Agentic AI, Predictive analytics, Machine Learning platforms, and AI-enabled enterprise applications.
Assess existing technology landscapes and define AI/ML modernization and transformation strategies.
Identify opportunities to leverage AI/ML across business functions and enterprise platforms.
Design architectures spanning data, AI/ML models, applications, APIs, cloud infrastructure, security, and integration.
Define enterprise strategies for LLM and foundation-model adoption, including model selection, hosting, fine-tuning, inference, and lifecycle management.
Establish architecture patterns for RAG, vector search, embeddings, AI agents, tool calling, orchestration, and multimodal AI.
Define enterprise AI platform architecture supporting experimentation, development, deployment, monitoring, and reuse.
Establish MLOps and LLMOps architecture and standards.
Define frameworks for model lifecycle management, model evaluation, monitoring, observability, and continuous improvement.
Partner with Data Architects to establish the data architecture required for AI/ML workloads.
Work with Security and Risk teams to establish AI security, privacy, responsible AI, and compliance architecture.
Define controls for data protection, model security, prompt injection, data leakage, access control, model governance, and AI risk management.
Evaluate AI/ML technologies, platforms, vendors, and emerging technologies.
Lead architecture reviews and provide technical governance for strategic AI initiatives.
Define build-vs-buy and cloud-vs-on-premises technology strategies.
Establish reusable AI/ML components, platforms, APIs, patterns, and reference implementations.
Provide technical leadership to AI Architects, Data Architects, ML Engineers, Data Scientists, and Solution Architects.
Communicate AI/ML architecture strategies and recommendations to C-level executives, technology leadership, and business stakeholders.
Support strategic technology planning, investment decisions, RFPs, vendor evaluations, and large-scale transformation programs.