Responsibilities:

• Lead the technical design, development, and implementation of full stack serverless applications for the Digital Correspondence solution.
• Develop and consume RESTful APIs and FHIR resources to securely retrieve, manage, and present correspondence data.
• Integrate front-end portals and backend services with AWS cloud messaging services (AWS Pinpoint, AWS End User Messaging) to facilitate SMS and email notification workflows.
• Implement robust identity, authentication, and authorization controls (e.g., OAuth 2.0, OIDC, SMART on FHIR).
• Write clean, well-documented, testable, and efficient code while conducting rigorous peer code reviews.

Must-have Skills:

• Cloud-Native & Serverless Backend Expertise: Proven experience designing and building highly scalable, serverless backend APIs using AWS (Amazon Web Services) (Lambda, API Gateway, DynamoDB, and Node.js or Python.
• Modern Frontend Development: Hands-on proficiency building secure, responsive, and accessible web applications using modern JavaScript/TypeScript frameworks (e.g., React, Angular, or Vue).
• Healthcare Integration & Standards: Practical experience integrating with health informatics standards including HL7 FHIR and SMART on FHIR for secure health data exchange.
• Experience with Ontario Assets (such as the Provider Registry, Hospital Report Manager, etc)
• Experience with Ontario eReferral systems (such as Ocean, Novari etc.)

Desired Skills:

• AWS Certified Developer – Associate or AWS Certified Solutions Architect.
• Knowledge of synthetic health data generation and handling complex PHI/PII data securely in cloud environments.
• Generative AI & LLM Integration: Experience integrating foundational models into enterprise applications using Amazon Bedrock, including prompt engineering and managing token usage.
• Retrieval-Augmented Generation (RAG): Familiarity with building RAG architectures utilizing vector databases (like Amazon OpenSearch Serverless) to securely query unstructured healthcare correspondence or clinical notes.
• AI-Assisted Development: Proficiency using AI coding assistants (like GitHub Copilot, Amazon Q Developer, or Cursor) to accelerate the delivery of secure, well-tested code while adhering to enterprise privacy policies.
• Healthcare NLP: Experience utilizing natural language processing services (such as Amazon Comprehend Medical) to extract meaningful insights, entities, and relationships from raw, unstructured medical text.