Lead Software Developer – Java
| Company | Blanc Labs |
|---|---|
| Location | Toronto, ON, Canada |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | |
| Experience Level | Senior |
Requirements
- 7+ years of Full Stack Development experience in 2 or more popular programming languages like Java, Python, Node, Angular, Vue, React etc.
- JavaScript coding to map segment fields.
- Prior Interface Development experience.
- Prior Healthcare (EMR/HIS/CIS) integration experience.
- Minimum of 3 years of experience in developing solutions for the healthcare industry, preferably on large healthcare interoperability projects.
- Experience analyzing sample HL7 messages, and developing HL7 ADT, ORM, ORU, SIU, MDM, DFT, e-Referral interfaces using Rhapsody Interface Engine.
- Familiarity with key healthcare terminologies and classifications such as SNOMED-CT, LOINC, ICD-10-CA/CCI, EMPI.
- Experience in building Restful APIs & developing system integrations.
- Experience working with SQL & NoSQL databases.
- Experience working with Docker, Kubernetes, and container platforms.
- Experience building multi-cloud systems that work in AWS, Azure, and GCP.
- Experience writing JavaScript that is maintainable, object-oriented, and sensitive to different browser technologies.
- Experience with modern version control and ticketing systems Like git, GitHub, Bitbucket and Jira.
Responsibilities
- Build and maintain robust front-end and back-end systems to ensure scalable, high-performing solutions.
- Develop APIs and implement integration layers to support seamless interaction between multiple platforms, including AI and RPA tools.
- Work cross-functionally with data scientists, AI engineers, and business analysts to ensure alignment between technical solutions and business objectives.
- Implement automated testing and deployment pipelines to improve system reliability and performance.
- Ensure compliance with privacy regulations and implement best practices for secure system design.
Preferred Qualifications
- Experience working with Large Language Models (LLMs) and retrieval-augmented generation (RAG) systems.
- Understanding of synthetic data generation for testing purposes.
- Strong problem-solving abilities, with a focus on continuous improvement.