Principal Enterprise Architect, AI Health Cloud

Healthcare
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 10+ years of experience in solution and platform architecture, specifically in AI/ML systems.
  • 15+ years in overall solution architecture.
  • Proven track record in developing AI-powered healthcare or pharmacy platforms.
  • Experience with multi-agent systems and RPA tools.
  • Strong API development experience using .NET and C#.
  • Deep knowledge of cloud platforms (preferably Azure) and containerization technologies.
  • Expertise in Generative AI, RAG architectures, and agentic AI orchestration.

Responsibilities

  • Architect and implement full stack AI/ML platform and solution architectures.
  • Design and develop scalable APIs and microservices using .NET and RESTful services.
  • Define platform and integration architecture standards for APIs and data security.
  • Collaborate with engineers to translate requirements into cloud-native solutions.
  • Optimize LLM-based systems and develop RAG pipelines.
  • Ensure compliance with healthcare standards like HIPAA and FHIR in all solutions.
  • Evaluate and integrate third-party AI services and open-source components.

Benefits

  • Opportunity to shape the future of AI in healthcare.
  • Collaborative work environment with engineers and clinicians.
  • Competitive compensation and benefits package.
  • Mission-driven organization focused on healthcare transformation.
Full Job Description
Overview

We are seeking a highly experienced and hands-on Principal Enterprise Architect to lead the full stack design and integration of advanced AI/ML platform and solution architectures within our AI-enabled Health Cloud Platform. This role combines deep expertise in end to end systems architecture, platform engineering, and integration/API design, enabling seamless, secure, and scalable AI/ML healthcare applications.

You will play a critical role in shaping both the technical foundation of the platform and the delivery of intelligent healthcare solutions, ensuring that AI capabilities such as Generative AI, Agentic AI, RPA, and fine-tuned RAG/Vector DB models are effectively embedded into clinical and pharmacy workflows.

Responsibilities
  • Architect and lead the full stack implementation of end-to-end AI/ML platform and solution architectures, ensuring seamless integration with enterprise systems and healthcare data sources.
  • Design and develop robust, scalable APIs and microservices using technologies such as .NET, C#, and RESTful services.
  • Define and enforce platform and integration architecture standards, including data contracts, API security, service orchestration, and interoperability.
  • Collaborate with AI/ML engineers, product managers, API, and data engineers to translate business and clinical requirements into cloud-native, reusable platform capabilities and solution-specific workflows.
  • Architect and optimize LLM-based systems, including RAG pipelines, vector databases, and agentic AI frameworks (e.g., LangChain, AutoGen).
  • Design and evolve the AI/ML platform architecture, including model lifecycle management, orchestration layers, and reusable AI services.
  • Ensure all solutions and platform components are HIPAA-compliant, secure, and aligned with healthcare interoperability standards (FHIR, HL7 etc.).
  • Evaluate and integrate third-party AI services, open-source tools, and cloud-native components into the platform.
  • Provide architectural leadership across model training, deployment, monitoring, and retraining, ensuring scalability and performance.
Qualifications
  • 10+ years of experience in solution and platform architecture, with a strong focus on AI/ML systems and enterprise integration.
  • 15+ years in overall solution architecture.
  • Proven experience designing and delivering AI-powered healthcare or pharmacy platforms and solutions.
  • Experience with multi-agent systems, RPA tools, and intelligent automation in healthcare.
  • Strong experience with API development and integration using .NET, C#, and modern API frameworks.
  • Deep understanding of cloud platforms (Azure preferred), containerization (Docker, Kubernetes), and MLOps practices.
  • Expertise in Generative AI, RAG architectures, vector databases, and agentic AI orchestration.
  • Expertise in healthcare data standards and secure data handling practices.
  • Excellent communication and stakeholder engagement skills.

Preferred Qualifications:

  • Background in AI/ML engineering, data science, or biomedical informatics.
  • Knowledge of responsible AI, model explainability, and bias mitigation.
  • Advanced degree (MS or PhD) in Computer Science, AI/ML, or a related field.
Additional Job Information

Why Join Us?

  • Architect the future of AI in healthcare by shaping both platform capabilities and solution delivery.
  • Collaborate with a forward-thinking team of engineers, clinicians, and product leaders.
  • Enjoy a highly competitive compensation and benefits package.
  • Be part of a mission-driven organization focused on transforming healthcare through intelligent technology.

 

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