Healthcare AI Solutions Engineer

Transform healthcare with us.

At Qualified Health, we’re redefining what’s possible with Generative AI in healthcare. Our infrastructure provides the guardrails for safe AI governance, healthcare-specific agent creation, and real-time algorithm monitoring—working alongside leading health systems to drive real change.

This is more than just a job. It’s an opportunity to build the future of AI in healthcare, solve complex challenges, and make a lasting impact on patient care. If you’re ambitious, innovative, and ready to move fast, we’d love to have you on board.

Join us in shaping the future of healthcare.

Job Summary:

Qualified Health is seeking a Healthcare AI Solutions Engineer to serve as a technical implementation specialist and forward-deployed consultant for our healthcare data integration and AI initiatives. This is a fast-paced, high-ownership role for someone who thrives in dynamic environments, takes initiative, and drives outcomes without waiting to be told what to do next.

In this hands-on consulting role, you’ll design and build robust data pipelines that transform raw healthcare data from diverse sources (Epic, LIMS, PACS, SharePoint, etc.) into production-ready datasets powering our AI platform—while also acting as a trusted technical advisor to our health system partners. You will leverage AI-assisted code development to accelerate delivery and set a new standard for what’s possible at the intersection of healthcare data and artificial intelligence.

We are looking for critical thinkers who can independently diagnose ambiguous problems, architect creative solutions, and communicate technical findings clearly to both technical and non-technical audiences. You must be comfortable operating with a consultant’s mindset—adapting quickly to new partner environments, earning trust through quality of work, and delivering results under tight timelines.

You own: Technical implementation, ETL development, data quality validation, pipeline construction, troubleshooting, and production deployment execution, and partner-facing technical consulting

Manager owns: Partner relationships, requirements gathering, timeline management, stakeholder communication, issue escalation, and ensuring delivery meets expectations

Together you deliver: Successful data integrations that meet partner needs on time with high quality

This is a technical role for someone who loves working with data, enjoys solving puzzles, and takes pride in building reliable, production-grade solutions.

 

Key Responsibilities:

Technical Implementation & Development

• Design and build ETL pipelines using PySpark, SQL, and Azure data services to process healthcare data from multiple source systems
• Execute data extraction and transformation operations on complex healthcare datasets, ensuring accuracy and compliance with established standards
• Develop data quality validation frameworks to identify and resolve issues during integration, QC, and backtesting phases
• Troubleshoot technical issues including data schema mismatches, transformation logic errors, and performance bottlenecks -- independently diagnosing root causes and driving resolution
• Build reusable data components and standardized integration patterns that accelerate future implementations
• Optimize pipeline performance for large-scale healthcare datasets, ensuring efficient processing and resource utilization
• Implement data validation rules specific to healthcare contexts (e.g., clinical code validation, temporal logic checks, referential integrity)
• Write and maintain technical documentation for data pipelines, transformations, and integration patterns
• Support production deployments by coordinating with infrastructure teams and conducting final testing
• Leverage AI-assisted code development tools to accelerate delivery and improve solution quality

Client Consulting & Collaboration

• Serve as a trusted technical advisor to health system partners, translating complex data and AI concepts into clear, actionable guidance
• Partner with Data Integration Manager to translate partner requirements into precise technical specifications
• Participate in technical discussions with partner IT teams to understand data schemas, access methods, and integration constraints
• Provide expert guidance on data mapping specifications, transformation approaches and architecture decisions
• Identify data quality issues and work with Manager to coordinate resolution with partners
• Communicate technical findings from QC and backtesting clearly to both technical and non-technical stakeholders
• Adapt consulting approach and communication style to the culture and maturity of each partner enviornment
• Contribute to continuous improvement of tools, processes, and technical standards

Product Prototyping & Innovation

• Support rapid prototyping of new AI-powered product features and data capabilities in close collaboration with product and engineering teams
• Translate partner use cases and field insights into prototype solutions that demonstrate the potential of the Qualified Health platform
• Build and iterate on proof-of-concept integrations and analytical tools to test new approaches before full-scale implementation
• Leverage AI-assisted development practices to compress prototyping cycles and explore solutions at speed
• Document learnings and outcomes from prototyping efforts to inform product roadmap decisions and reusable patterns
• Bring a builder’s mindset to ambiguous problem spaces, moving quickly from idea to working demonstration

Required Qualifications:

• 5+ years of experience in data analytics, data engineering, or solution delivery roles, with demonstrated expertise in data integration and ETL processes
• Strong analytical toolkit with proficiency in:
  • PySpark for distributed data processing
  • Advanced SQL for data querying and transformation
  • Excel for data analysis and reporting
• Production ETL experience: Track record of building and maintaining production-grade data pipelines with proper error handling and monitoring
• Data quality focus: Experience implementing validation frameworks and troubleshooting data quality issues
• Healthcare data experience: Prior work with healthcare datasets (EHR, claims, clinical, lab data)
• Consultant mindset: ability to earn trust quickly, communicate complex ideas to diverse audiences, and deliver value in client-facing environments 
• Ownership Mentality: takes full accountability for the quality and outcome of your work from scoping through production
• Attention to detail: Commitment to accuracy, testing, and delivering reliable solutions
• Collaborative working style: Comfortable partnering with non-technical colleagues and adapting to feedback
• Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or related technical field

Preferred Skills:

• Epic Clarity experience: Direct work with Epic's relational database structure and clinical data models
• Healthcare data standards knowledge: Understanding of FHIR, HL7v2, DICOM, LOINC, SNOMED, ICD-10
• Azure cloud platform: Hands-on experience with Azure Databricks, Data Factory, Blob Storage, Delta Lake