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Hl7 Integration Developer Jobs in Montana (NOW HIRING)

As our Lead AI Engineer, you'll serve as the principal technical leader responsible for designing ... Experience integrating with Epic or another electronic health record, FHIR, HL7, clinical data ...

Hl7 Integration Developer information

What does an HL7 Integration Developer do?

An HL7 Integration Developer specializes in designing, developing, and maintaining interfaces that allow healthcare systems to exchange data using HL7 standards. They work closely with hospitals, clinics, and software vendors to ensure patient information flows smoothly and securely between various electronic health record (EHR) systems. Their responsibilities also include troubleshooting integration issues, implementing new data exchange solutions, and ensuring compliance with healthcare regulations. Strong knowledge of HL7 protocols, healthcare IT systems, and programming languages is essential for this role.

What are the key skills and qualifications needed to thrive as an HL7 Integration Developer?

To excel as an HL7 Integration Developer, you need strong programming skills (often in languages like Java, C#, or Python), in-depth knowledge of HL7 messaging standards, and experience with healthcare interoperability. Familiarity with integration engines such as Mirth Connect, Cloverleaf, or Rhapsody, and relevant certifications like HL7 or FHIR, are highly beneficial. Strong problem-solving, attention to detail, and effective communication skills set top performers apart. These skills are crucial for ensuring seamless data exchange, maintaining compliance, and supporting efficient healthcare workflows.

What are some common challenges faced by HL7 Integration Developers when working with multiple healthcare systems?

HL7 Integration Developers often encounter challenges related to varying interpretations of HL7 standards across different healthcare systems. Each hospital or vendor may customize HL7 messages, requiring developers to adapt interfaces and handle exceptions. Additionally, managing data consistency and ensuring secure, real-time data exchange can be complex due to legacy systems or limited documentation. Effective communication with clinical, technical, and vendor teams is essential to troubleshoot issues and deliver seamless integrations.

What is the difference between Hl7 Integration Developer vs Hl7 Interface Analyst?

AspectHl7 Integration DeveloperHl7 Interface Analyst
CertificationsHL7, healthcare IT certificationsHL7, healthcare IT certifications
Work EnvironmentHealthcare IT teams, software developmentHealthcare facilities, IT support teams
Employer & IndustryHospitals, healthcare vendors, EHR vendorsHospitals, clinics, healthcare organizations
Primary FocusDeveloping and maintaining HL7 interfaces and integrationsAnalyzing, troubleshooting, and supporting HL7 interfaces

The main difference is that Hl7 Integration Developers focus on creating and implementing HL7 interfaces, while Hl7 Interface Analysts primarily troubleshoot and support existing HL7 systems. Both roles require similar certifications and work within healthcare IT environments, but their responsibilities differ in development versus support functions.

What are popular job titles related to Hl7 Integration Developer jobs in Montana?

For Hl7 Integration Developer jobs in Montana, the most frequently searched job titles are:

What job categories do people searching Hl7 Integration Developer jobs in Montana look for?

The top searched job categories for Hl7 Integration Developer jobs in Montana are:

What cities in Montana are hiring for Hl7 Integration Developer jobs?

Cities in Montana with the most Hl7 Integration Developer job openings:

Senior AI Engineer - IT AI and Data Technology

Helena, MT โ€ข On-site

St. Peter's Health
Health Care and Social Assistanceย โ€ขย 1 - 5K employees

$95K - $129K/yr

Full-time

Re-posted 3 days ago


Job description


Lead the future of healthcare AI at St. Peter's Health! As our Lead AI Engineer, you'll serve as the principal technical leader responsible for designing, building, and scaling enterprise AI solutions that improve clinical and business operations. You'll partner closely with the Director of AI to establish the organization's AI platform, architecture, engineering standards, and best practices while mentoring a growing engineering team. This hands-on leadership role combines software architecture, cloud-native engineering, MLOps/LLMOps, and applied AI-including generative AI, machine learning, NLP, and intelligent agents-to deliver secure, reliable, and impactful production solutions across the health system. If you're passionate about building enterprise AI from the ground up and driving innovation in healthcare, this is an opportunity to make a lasting impact.
KNOWLEDGE/EXPERIENCE:
Required:
  • Ten or more years of progressive professional experience in software engineering, application architecture, platform engineering, distributed systems, or related technology work, including at least three years of hands-on experience deploying and operating production AI/ML systems.
  • Qualifying production AI experience may include traditional machine learning, natural language processing, computer vision, recommender systems, predictive modeling, generative AI, or related applied AI systems.
  • Advanced software engineering and architecture proficiency in Python and strong working proficiency in one or more additional enterprise programming languages such as C#, Java, TypeScript, or Go.
  • Demonstrated experience architecting and operating distributed, cloud-native applications, APIs, data services, containers, automated delivery pipelines, infrastructure automation, and production observability.
  • Deep working knowledge of the production AI/ML lifecycle, including model and service integration, retrieval, agents, evaluation, MLOps or LLMOps, monitoring, reliability, governance, security, and cost optimization.
  • Demonstrated ability to lead architecture decisions, mentor senior engineers, coordinate complex technical workstreams, communicate with executives and stakeholders, and guide production outcomes across teams.

Preferred:
  • Experience in a healthcare provider, payer, health system, life sciences, financial services, or other highly regulated environment.
  • Experience integrating with Epic or another electronic health record, FHIR, HL7, clinical data, medical terminology, or healthcare operational systems.
  • Experience establishing enterprise AI or ML platform architecture on Microsoft Azure, AWS, Google Cloud, or a comparable large-scale cloud environment.
  • Experience leading MLOps or LLMOps, retrieval-augmented generation, semantic or vector search, agentic systems, model evaluation, and AI application observability at production scale.
  • Strong working knowledge of HIPAA, HITECH, healthcare privacy, information security, data governance, responsible AI, clinical safety, and audit requirements.
  • Experience evaluating vendors, leading build-versus-buy decisions, defining reference architectures, and establishing engineering standards for a growing technical organization.

EDUCATION:
Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Systems, Data Science, Applied Mathematics, Statistics, or a related field is preferred. Equivalent combinations of education, advanced technical training, certifications, and directly relevant professional experience may be considered.
A master's degree in a related field is preferred. Advanced education may substitute for a portion of the required experience when accompanied by demonstrated enterprise software architecture, production engineering, and AI deployment capability.