CTC is looking for an AI Integration Engineer to help design, build, and integrate next-generation healthcare technology solutions in Michigan. This is a role for an engineer who enjoys connecting complex systems and data, and who sees real value in using AI to improve healthcare operations and patient outcomes. As AI Integration Engineer, you’ll design and support integrated solutions that use AI and cloud platforms; work with business, clinical, and technical stakeholders to deliver scalable and secure systems; build and maintain integrations between enterprise systems, applications, and data platforms; develop workflows using large language models and agentic AI frameworks; work with data platforms such as Snowflake to ingest, transform, and analyze structured and unstructured healthcare data; apply strong software engineering practices in testing, troubleshooting, and performance work; take part in architecture discussions and innovation initiatives; ensure every solution meets healthcare security, privacy, and compliance requirements; and support deployment, monitoring, and ongoing improvement. The position is full-time and suits an engineer with a computer science or related degree, or equivalent experience, and hands-on exposure to AI technologies.
About the Team — Healthcare Technology & AI Integration
Company: CTC
Location: Michigan, United States
Focus: Healthcare technology solutions powered by AI and cloud platforms
Data: Structured and unstructured healthcare data on modern platforms
Standards: Security, privacy, and healthcare compliance
AI Integration Engineer Role — Systems, Data & AI Workflows
Department: Engineering & Integration
Primary Focus: System integration, LLM workflows, healthcare data pipelines
Scope: Enterprise systems, applications, and data platforms
Mission: Delivering secure, scalable healthcare solutions that use AI responsibly
AI Integration Engineer Position Overview
The AI Integration Engineer role sits where software engineering, healthcare data, and artificial intelligence meet. You’ll help design and support integrated technology solutions that connect enterprise systems, applications, and data platforms, so that information moves reliably between the tools that clinical and business teams depend on. Much of the work is about integration. You’ll build and maintain the connections between systems, design the APIs and data flows that carry information between them, and make sure those flows hold up under real operating conditions. AI is central to the role. You’ll develop workflows that use large language models and agentic AI frameworks, turning them into practical tools that help people work more effectively. Data work is a major part of the picture too. You’ll use platforms such as Snowflake to ingest, transform, and analyze structured and unstructured healthcare data, always with an eye on quality and governance. Collaboration runs throughout. You’ll work with business, clinical, and technical stakeholders to understand what they need, and you’ll contribute to architecture discussions and innovation initiatives that shape the future of AI-driven healthcare applications. Because the data involved is sensitive, security, privacy, and compliance requirements are built into your design and testing from the start. Once solutions are live, you’ll help with deployment, monitoring, and ongoing enhancement, troubleshooting issues and improving performance over time.
As AI Integration Engineer, you’ll build depth in healthcare interoperability, cloud data platforms, and the practical engineering that makes AI systems reliable in regulated environments. The ideal candidate holds a bachelor’s degree in computer science, engineering, information systems, or a related field, or brings equivalent experience, along with solid engineering fundamentals in object-oriented programming, API development, system architecture, data structures, algorithms, and CI/CD practice. Hands-on experience with large language models, agentic AI frameworks, or AI-powered application development is essential, as is experience with Snowflake or a similar cloud data platform. Preferred experience includes integration engineering, healthcare interoperability standards such as HL7 and FHIR, and integration with electronic health records, practice management, or revenue cycle platforms. Familiarity with Azure, AWS, or Google Cloud, and an understanding of HIPAA and healthcare data governance, will strengthen your application. For engineers in Michigan who want to apply AI to better healthcare operations and patient outcomes, this role offers a meaningful place to build a career.
Why This Role Matters: As AI Integration Engineer in healthcare technology, you help clinical and business teams work with better information, build the integrations that connect electronic health records and data platforms, bring LLM and agentic AI workflows into practical use, protect sensitive data through strong security and compliance, collaborate across global teams, and build an engineering career at the intersection of AI and healthcare.
Key Responsibilities & Engineering Duties
AI Solution Design & Development
- Design integrated solutions that use AI and cloud platforms
- Develop applications that use large language models
- Build workflows using agentic AI frameworks
- Support AI-powered application development
- Evaluate AI approaches for healthcare use cases
- Contribute to innovation in AI-driven healthcare applications
System Integration & APIs
- Build and maintain integrations between enterprise systems
- Connect applications and data platforms through APIs
- Design reliable data flows between systems
- Troubleshoot integration issues across environments
- Document integration architecture and interfaces
- Support middleware and event-driven integration patterns
Healthcare Data Engineering
- Ingest structured and unstructured healthcare data
- Transform data for analysis and downstream use
- Work with Snowflake and cloud data platforms
- Support data quality and consistency checks
- Help build healthcare data pipelines
- Maintain data accuracy across integrated systems
Software Engineering Practice
- Apply object-oriented programming and sound system design
- Write tests and support testing practices
- Troubleshoot and optimize system performance
- Follow CI/CD and DevOps principles
- Participate in code and architecture reviews
- Support deployment and ongoing enhancement
Stakeholder Collaboration
- Work with business, clinical, and technical stakeholders
- Translate requirements into scalable solutions
- Take part in architecture discussions
- Communicate technical concepts to non-technical audiences
- Collaborate effectively within a global team
- Share progress and risks clearly
Security, Compliance & Operations
- Ensure solutions meet security and privacy requirements
- Follow healthcare compliance and data governance standards
- Support monitoring of deployed integration solutions
- Respond to operational issues in production
- Apply secure development practices throughout
- Balance innovation with regulatory requirements
Qualifications & Requirements
Education
- Bachelor’s degree in Computer Science or Engineering
- Bachelor’s degree in Information Systems or a related field
- Equivalent experience accepted
Software Engineering Fundamentals
- Object-oriented programming
- API development and integration
- System architecture and design patterns
- Data structures and algorithms
- CI/CD and DevOps principles
AI & Data Experience
- Hands-on experience with large language models (LLMs)
- Experience with agentic AI frameworks
- Experience building AI-powered applications
- Experience with Snowflake or similar cloud data platforms
Preferred Qualifications
- Integration engineering experience
- Knowledge of HL7 and FHIR interoperability standards
- Experience with EHR, EMR, practice management, or revenue cycle systems
- Familiarity with Azure, AWS, or Google Cloud Platform
- Understanding of HIPAA and healthcare data governance
- Experience with API management, middleware, and event-driven architecture
Professional Skills
- Strong problem-solving and analytical skills
- Strong communication skills
- Ability to work in a collaborative, global team
- Self-motivation and ability to work independently
Career Development & Growth Opportunities
Professional Advancement
- Pathway toward Senior AI Engineer or Integration Architect roles
- Opportunity to lead AI and integration programs
- Growth into healthcare data engineering and MLOps
- Influence on architecture and innovation direction
Learning & Development
- Hands-on work with LLMs and agentic AI frameworks
- Experience with healthcare interoperability standards
- Exposure to cloud platforms and modern data stacks
- Development in healthcare data governance and security
About the Team — Technology That Improves Healthcare
This healthcare technology team designs and delivers solutions that connect enterprise systems and clinical data, using AI and cloud platforms to improve healthcare operations. Its work emphasizes secure, scalable integration, responsible use of AI, and close collaboration between engineers, clinicians, and business stakeholders. The team values people who can balance innovation with the regulatory and operational demands of healthcare.
Career Excellence in Healthcare AI: Join a healthcare technology team in Michigan, build integrations and AI workflows that connect clinical systems, work with Snowflake and cloud data platforms, apply FHIR and HL7 standards, and grow an engineering career at the intersection of AI and patient care.
Who Should Apply?
- Software Engineers: Ready to work on AI-enabled systems
- Integration Engineers: Moving into healthcare interoperability
- Data Engineers: Working with Snowflake and healthcare data
- Computer Science Graduates: Starting a career in AI and healthcare
- FHIR and HL7 Developers: Seeking an AI-focused role
- Machine Learning Engineers: Interested in LLM applications in healthcare
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