Enterprise Architect (AI focus) - CONTRACT

Contract, 1099 engagement for a 6-month duration starting in early August. 40 hours per week on-site in Salt Lake City, UT.

About the role

Lead the design, strategy, and implementation of AI-enabled systems and intelligent platforms across the enterprise. Define how AI is responsibly and effectively integrated into the client's ecosystem, leveraging strong foundations in data architecture, APIs, and event-driven systems to drive innovation, personalization, and operational efficiency. This position offers the opportunity to shape the technological landscape and drive transformative change.

Responsibilities

• AI Architecture Leadership
  • Define and lead the client's enterprise AI architecture strategy, including reference architectures and best practices.
  • Establish patterns for integrating AI/ML and generative AI (e.g., LLMs) into enterprise systems.
  • Drive alignment between AI initiatives and institutional priorities (student success, personalization, operational efficiency).
• AI Solutions Design & Enablement
  • Architect scalable AI solutions such as recommendation systems, intelligent assistants, and automation workflows.
  • Define reusable AI services and platforms (e.g., model serving, prompt orchestration, inference pipelines).
  • Guide build vs. buy decisions for AI platforms and tooling.
• Data & AI Foundations
  • Ensure robust data architecture to support AI/ML (feature engineering, data pipelines, data quality).
  • Partner with data engineering and data science teams to enable MLOps and model lifecycle management.
  • Promote data-as-a-product principles to support AI use cases.
• API & Integration Strategy
  • Design APIs and service layers to expose AI capabilities across the enterprise.
  • Enable integration of AI services into applications through secure, scalable API frameworks.
  • Support composable architectures that embed AI into workflows.
• Event-Driven & Real-Time AI
  • Leverage event-driven architecture (EDA) to enable real-time AI use cases.
  • Design streaming pipelines for inference, feedback loops, and adaptive systems.
  • Define event contracts and ensure interoperability across domains.
• Responsible AI & Governance
  • Establish frameworks for ethical, secure, and compliant AI usage (e.g., bias mitigation, transparency, FERPA alignment).
  • Define governance for model usage, data privacy, and AI lifecycle oversight.
  • Partner with legal, security, data science, MLOps, and compliance teams.
• Cross-Functional Leadership
  • Collaborate with product, engineering, data science, MLOps, and academic stakeholders.
  • Mentor architects, engineers, and AI practitioners.
  • Influence enterprise-wide adoption of AI capabilities.

Requirements

• 10+ years in software engineering, architecture, or related roles, with increasing focus on AI/ML systems.
• 3 years as an Enterprise or Solution Architect or 8 years in a technical leadership role (e.g., technical lead, principal engineer).
• Proven experience designing enterprise-scale distributed systems and delivering a successful technology transformation.
• Proven experience designing and deploying AI/ML or generative AI solutions at scale.
• Strong expertise in:
  • AI/ML architecture (training, inference, deployment patterns)
  • APIs and microservices for AI integration
  • Distributed systems and cloud platforms (AWS, Azure, or GCP)
• Experience with data architecture and pipelines supporting AI workloads.
• Ability to translate business needs into AI-enabled solutions.

Preferred Qualifications

• Experience with LLMs, prompt engineering, RAG architectures, and vector databases.
• Familiarity with MLOps tools and frameworks (e.g., MLflow, SageMaker, Vertex AI).
• Familiarity with modern data stack tools (e.g., Snowflake, Databricks, dbt, Kafka).
• Certifications (e.g., TOGAF, AWS/Azure Architect) are a plus.