Enterprise Information Management Solution Architect

Stanford Health Care • Palo Alto, CA

3d • $94 - $125 • Hybrid

About The Position

The Principal Enterprise Information Management (EIM) Solution Architect will lead the design, development, governance and implementation of an advanced Information Management platform and related solutions across Stanford Health Care and School of Medicine. They will be responsible for the architectural blueprint for a logical mesh architecture that enables access to a wide range of data from across the enterprise for numerous use cases including: operational analytics, research studies, exploratory adhoc analysis, AI/ML solution development and deployment, integration with LLM's and other AI technologies, vendor partnerships, etc. They are expected to stay current with changes in the market and regularly re-evaluate and adjust the blueprint to take advantage of new technologies to enable innovation that drives measurable value to patient outcomes, quality of care, and financial results.
This is a Stanford Health Care job.

The Principal Enterprise Information Management (EIM) Solution Architect will lead the design, development, governance and implementation of an advanced Information Management platform and related solutions across Stanford Health Care and School of Medicine. An ideal candidate understands the complexities of, and can drive innovation with, integrating and developing large scale data platforms that support Analytical and AI/ML use cases within a complex healthcare environment. The individual should have a point of view and speak to related and innovative design and implementation architectures with authority and back it up with detailed technical knowledge and experience. The role will include analyzing, testing, and proposing architectures to support a broad range of projects and business problems while ensuring interoperability and design best practices can be established and maintained across SHC and our external partners, vendors and entities. The candidate should be knowledgeable of data management (including AI/ML) standards, regulations, privacy and security implications in a regulated industry.

Requirements

• Bachelor's Degree in Computer Science, Business Administration, Management, Data Science, AI/ML or a related field required.
• A minimum of 6+ years of experience in IT required.
• Experience with machine learning frameworks (TensorFlow, PyTorch, etc).
• Experience with cloud AI ecosystems (AWS SageMaker, Azure ML or Google Vertex AI, LLMs like ChatGPT, Claude, Gemini, etc).
• Solid understanding of vector and graph databases, LLMs, RAG, MCP, Agents and ML Ops.
• Strong understanding of data architectures, APIs, microservices and event-driven technologies.
• Experience with healthcare data standards (HOPAA, EDI, FHIR).
• In-depth experience of designing and implementing EIM solutions.
• Experience in architecture practice, tools, and methodologies.
• Demonstrate the ability to work well with others and exhibit leadership.
• Have a track record of remaining unbiased toward specific technologies or vendors.
• Be an excellent communicator and collaborator, engaging with multiple technical and business stakeholders and leaders.
• Be able to translate the EIM architecture contribution to business outcomes into simple briefings for use by various business-operations-technical-leadership roles.
• Organizationally savvy, with a good understanding of the enterprise's political climate and how to navigate, influence and persuade political waters.
• Ability to communicate, influence and persuade peers and leadership.
• Ability to understand the long-term ("big picture") and short-term perspectives of situations.
• Ability to quickly comprehend the functions and capabilities of new technologies.
• Displays intellectual curiosity and integrity.

Nice To Haves

• Master's Degree in Computer and Information Science, Business Administration, Management or a related field preferred.
• Or equivalent experience.

Responsibilities

• Influence EIM vision, architecture and technology strategy: By partnering with business unit leadership, and through the rationalization of solution value chains, this individual will provide strategic recommendations to maximize the value of technologies via their creation, access and use.
• Maximize value derived from EIM solutions: Foster value creation using the organization's data assets, as well as the external data ecosystem.
• Enable Data Science and AI Readiness: Ensure underlying data strategy across SHC allows EIM platforms and technologies to leverage structured, governed and discoverable data through inline pipelines.
• Surface information priority: Assess the benefits and the risks of information by using tools such as business capability models to create an information-centric view to quickly visualize what information matters most to the organization based on the defined business strategy.
• Enhance decision making: Use tools such as business information models to provide the organization with a future-state view of the EIM landscape that is unencumbered by the specific implementation details imposed by proprietary solutions or technologies. Assist decision design.
• Enable effective data and analytics governance: Suggest who can take what actions with what information, and under what circumstances. Assist data and analytics leaders, and business and IT leadership in developing EIM governance processes and structures.
• Technology evaluation: Evaluate and review integration of enterprise-grade EIM platforms, LLMs, vector and graph databases and orchestration.
• Manage risk: Aid the definition of data classifications, ensure alignment to current and future governance review processes, policies and monitoring.
• Strategic Alignment and Enterprise Scalability: Align EIM and AI architecture with Stanford Healthcare’s enterprise transformational roadmap and analytics strategy.
• Secure AI/ML assets: Aid in the analysis of security requirements and solutions, and work with the chief information security officer (CISO) [and CDAO] to ensure that enterprise AI, ML, data and analytics assets are treated as protected assets.
• Foster cross Enterprise collaboration: Lead efforts to test, evaluate and adopt internally developed EIM technologies and related solutions. Drive to expand and standardize EIM solutions, adhering to internal and industry standards and best practices. Help internal business leaders with knowledge sharing of internal EIM capabilities and technologies that can be leveraged to solve defined problem statements.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level