Impress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Tailor your resume to this Enterprise Architect - AI/ML - New York role.
Rezi rewrites your resume against Photon's job description. Free.
Tailor your resume to this Enterprise Architect - AI/ML - New York role.
Rezi rewrites your resume against Photon's job description. Free.
Don't guess if your resume is good enough.
See how it scores against the Enterprise Architect - AI/ML - New York posting at Photon — free, in seconds.
Don't guess if your resume is good enough.
See how it scores against the Enterprise Architect - AI/ML - New York posting at Photon — free, in seconds.
About the Role
Define and lead the enterprise-wide architecture strategy for Artificial Intelligence, Machine Learning, Generative AI, and emerging AI technologies. Establish AI/ML architecture principles, technology strategy, reference architectures, governance frameworks, and adoption roadmaps. Partner with business and technology leaders to transform AI opportunities into scalable, secure, and business-aligned solutions.
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.
Requirements
- Strong enterprise architecture expertise.
- Deep knowledge of AI/ML, Generative AI, cloud, data platforms, application architecture, security, and AI governance.
Skills
- AI/ML
- Generative AI
- Cloud
- Data Platforms
- Application Architecture
- Security
- AI Governance
- LLM
- Foundation Models
- RAG
- Vector Search
- Embeddings
- AI Agents
- Tool Calling
- Orchestration
- Multimodal AI
- MLOps
- LLMOps
- Model Lifecycle Management
- Model Evaluation
- Monitoring
- Observability
- Continuous Improvement
- Data Architecture
- AI Security
- AI Privacy
- Responsible AI
- Compliance Architecture
- Data Protection
- Model Security
- Prompt Injection
- Data Leakage
- Access Control
- Model Governance
- AI Risk Management
- Build-vs-buy strategies
- Cloud-vs-on-premises strategies
Work Type
- Full-time
Experience Level
- Experienced
Salary/Compensations
- USD 62,000 - USD 217,000
Benefits
- Medical benefits
- Vision benefits
- Dental benefits
- 401k retirement plan
- Variable pay/incentives
- Paid time off
- Paid holidays