
Healthcare AI Solutions Engineer (Remote)
Jobright.ai · United States
- Hybrid
- Full-time
- $175,000 / year
- United States
Job highlights
- Design and build ETL pipelines for healthcare data.
- Process and transform complex healthcare datasets.
- Develop data quality validation frameworks.
- Troubleshoot data integration and transformation issues.
- Act as a technical advisor to health system partners.
About the role
Healthcare AI Solutions Engineer
This role is part of the Jobright TNT - the private hiring network connecting top talent with top AI startups like Perplexity, Mercor, Cresta, Suno and 150 more. This is not a mass job posting. Only select, high-signal candidates are invited to Jobright TNT and recommended directly to hiring teams.
Hiring Company: Qualified Health
One-liner: Qualified Health is building a healthcare-native enterprise AI platform that helps leading health systems deploy AI safely and effectively.
Salary: $130K/yr - $200K/yr
Why Join Us:
Not specified, but the opportunity to work with leading AI startups and build a healthcare-native enterprise AI platform is a significant draw.
Role Responsibilities
- 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.
- 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 environment.
- Contribute to continuous improvement of tools, processes, and technical standards.
- 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.
Qualifications
Required
- 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
- 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.
- Healthcare compliance awareness: Understanding of HIPAA requirements and healthcare data security best practices.
- Data warehouse/lakehouse experience: Familiarity with dimensional modeling and modern data architecture patterns.
- DevOps practices: Experience with Git, CI/CD pipelines, and infrastructure-as-code.
- Performance tuning: Proven ability to optimize complex data transformations for scale.
- LIMS/PACS experience: Prior work integrating laboratory or imaging systems data.
- Multiple data format fluency: Experience with JSON, XML, Parquet, CSV, and other healthcare interchange formats.
- Experience with AI-assisted development tools (e.g., GitHub Copilot, Cursor, or similar) to accelerate coding and prototyping.
- Prior experience in a client-facing technical consulting, forward deployment, or solutions engineering role.
How can I join Jobright TNT:
If this is your first time applying to a Jobright TNT role, the process works as follows:
- Apply to your first Jobright TNT role.
- We review your background to determine if you meet the TNT quality bar.
- If qualified, your application is directly recommended to the employer.
- Once accepted into TNT, you may be:- Invited to apply for other exclusive TNT-only roles- Invited to private, invite-only hiring events with top startups.
You will be notified of your TNT selection result.
PS: All Jobright TNT roles are 100% real, directly hired by top AI startups we partner with, and come with priority review and higher response rates than the normal application queue.
Key skills/competency
- Healthcare Data Engineering
- AI Solutions Engineering
- ETL Pipeline Development
- PySpark
- Advanced SQL
- Azure Data Services
- Data Quality Validation
- Technical Consulting
- Healthcare Data Standards
- HIPAA Compliance
Skills & topics
- Healthcare AI
- Solutions Engineer
- Data Engineering
- ETL
- PySpark
- Azure
- SQL
- Remote
- AI Startups
- Healthcare Data
How to get hired
- Apply to the Jobright TNT role: Submit your application through the provided channel to initiate the process.
- Highlight relevant experience: Emphasize your 5+ years in data engineering, ETL, and healthcare data.
- Showcase technical skills: Detail your proficiency in PySpark, Advanced SQL, and Azure data services.
- Demonstrate a consultant mindset: Explain your experience communicating complex technical concepts to diverse audiences.
- Emphasize ownership and attention to detail: Provide examples of how you ensure accuracy and accountability in your work.
Technical preparation
Behavioral questions
Frequently asked questions
- How does the Jobright TNT application process for the Healthcare AI Solutions Engineer role work?
- The Jobright TNT process for the Healthcare AI Solutions Engineer role involves applying directly to the TNT role. Your background is reviewed to ensure you meet the TNT quality bar. If qualified, your application is then directly recommended to Qualified Health for priority consideration. Accepted candidates gain access to exclusive roles and private hiring events.
- What specific healthcare data experience is required for the Healthcare AI Solutions Engineer position?
- The Healthcare AI Solutions Engineer role requires prior work with healthcare datasets. This includes experience with EHR (Electronic Health Records), claims data, clinical data, and lab data. Familiarity with healthcare data standards like FHIR or HL7 is a plus.
- What are the key technical skills for the Healthcare AI Solutions Engineer role at Qualified Health?
- Key technical skills include 5+ years of experience in data integration and ETL processes, proficiency in PySpark for distributed data processing, Advanced SQL for data querying and transformation, and experience with Azure data services such as Azure Databricks and Data Factory. Experience with AI-assisted development tools is also beneficial.
- How does Qualified Health use AI in their enterprise platform for health systems?
- Qualified Health is building a healthcare-native enterprise AI platform designed to help leading health systems deploy AI safely and effectively. This involves processing healthcare data, building robust data pipelines, and developing AI-powered features and data capabilities to demonstrate the platform's potential.
- Is this a remote position for the Healthcare AI Solutions Engineer role?
- Yes, the Healthcare AI Solutions Engineer position is listed as a remote role. This allows flexibility in work location while contributing to a leading AI startup in the healthcare sector.
- What is the salary range for the Healthcare AI Solutions Engineer role?
- The salary range for the Healthcare AI Solutions Engineer role is competitive, offered between $130,000 and $200,000 per year, reflecting the specialized skills and experience required for this position.
- What does 'TNT quality bar' mean in the context of Jobright TNT applications?
- The 'TNT quality bar' refers to a set of criteria that Jobright uses to identify high-signal, qualified candidates. Meeting this bar means your application is directly recommended to the hiring company, ensuring priority review and a higher chance of response compared to standard applications.
- What are the 'preferred' qualifications for the Healthcare AI Solutions Engineer role, and how important are they?
- Preferred qualifications include experience with Epic Clarity, healthcare data standards (FHIR, HL7), Azure cloud services, HIPAA compliance, and data warehousing. While not strictly required, these preferred skills significantly strengthen your application and demonstrate deeper expertise relevant to the role's challenges.