Senior Artificial Intelligence (AI) Software Developer

Assignment: RQ00735 - Software Developer - Artificial Intelligence (AI) - Senior Requisition: RQ00735 Job Title: Senior Artificial Intelligence (AI) Software Developer for Referral RAG and MCP Client: Ontario Health Start Date: 2026-08-31 End Date: 2027-04-23 Department: Digital Excellence in Health Office Location: 525 University Avenue, Toronto Business Days: 164.00 Location: Hybrid (onsite as needed) Public Sector Experience: must have

Must Haves:

• Senior software development experience designing and implementing enterprise AI solutions.
• Experience developing Retrieval Augmented Generation (RAG) solutions using vector databases and semantic search.
• Experience developing AI agents using Model Context Protocol (MCP).
• Experience integrating Large Language Models with enterprise applications.
• Experience implementing healthcare AI solutions using FHIR R4/R4B, SMART on FHIR, and REST APIs.
• Experience developing Java Spring Boot and Python backend services supporting AI workloads.
• Experience with Health Services Directories
• Experience with AWS AI services including Amazon Bedrock and related AI services.
• Experience implementing vector search using OpenSearch
• Experience designing prompt orchestration, tool calling, and agent workflows.
• Experience implementing secure AI applications using OAuth2/OIDC and role-based authorization.
• Experience integrating AI solutions with healthcare provider directories and structured healthcare data.
• Experience evaluating AI accuracy, hallucination reduction, grounding, and response quality.
• Experience with AWS Bedrock

Description

• The Agency is expanding the Provincial Health Services Directory (PHSD) to incorporate artificial intelligence capabilities that improve provider discovery, referral quality, and healthcare navigation across provincial digital health applications. The solution will utilize PHSD provider, practitioner, organization, healthcare service, specialty, location, and service metadata together with clinical referral context to provide intelligent recommendations while maintaining traceability to authoritative source data. AI agents will consume PHSD FHIR APIs, Smile CDR, AWS HealthLake, the Agency Master Data Management, and other provincial digital health assets to provide grounded responses rather than generative opinions. The project includes development of reusable AI services, MCP servers, semantic search capabilities, vector-based retrieval, prompt orchestration, evaluation frameworks, and secure integration with SMART on FHIR applications and provincial healthcare systems. The implementation will emphasize explainability, auditability, privacy, security, and clinical confidence while supporting future AI-enabled healthcare workflows across the Agency.

Responsibilities:

• Design and develop AI agents supporting intelligent provider and referral destination discovery.
• Develop Retrieval Augmented Generation (RAG) pipelines utilizing PHSD healthcare data.
• Design and implement MCP servers exposing PHSD functionality to AI clients.
• Develop semantic search capabilities supporting provider, practitioner, organization, healthcare service, and specialty discovery.
• Integrate AI agents with Smile CDR, AWS HealthLake, PHSD APIs, Provider Registry, and Master Data Management services.
• Develop intelligent referral destination recommendations based on referral reason, specialty, geography, language, service availability, and organizational relationships.
• Develop AI services that validate referral completeness and identify missing referral information prior to submission.
• Implement explainable AI responses referencing authoritative PHSD records and supporting evidence.
• Develop prompt templates, orchestration workflows, tool selection strategies, and AI evaluation frameworks.
• Optimize retrieval quality, ranking, semantic search relevance, latency, and operational performance.
• Implement monitoring, evaluation, telemetry, audit logging, and continuous improvement processes for AI services.
• Produce technical documentation, AI governance documentation, operational procedures, and knowledge transfer materials.

Desired Skills:

• Experience developing AI solutions for healthcare provider directory, referral, scheduling, or care navigation systems.
• Experience implementing healthcare knowledge graphs or semantic healthcare search.
• Experience with Amazon Bedrock Agents or other enterprise AI orchestration platforms.
• Experience implementing MCP-based enterprise integrations.
• Experience developing AI evaluation frameworks including groundedness, factuality, retrieval accuracy, and hallucination detection.
• Experience implementing FHIR terminology services, SNOMED CT, LOINC, and healthcare ontologies.
• Experience with clinician-facing AI assistants and decision support tools.
• Experience with Responsible AI, privacy-preserving AI, explainability, and AI governance.
• Experience working with Agile delivery teams building enterprise healthcare AI platforms.

Required Skills:

• Enterprise AI application development using modern LLM frameworks and agent architectures.
• Retrieval Augmented Generation (RAG) architecture, semantic retrieval, vector embeddings, and knowledge grounding.
• Model Context Protocol (MCP) server development, tool integration, and agent orchestration.
• Prompt engineering, tool calling, structured outputs, evaluation frameworks, and AI workflow design.
• Integration of AI solutions with FHIR R4/R4B, SMART on FHIR, REST APIs, and healthcare interoperability standards.
• Java Spring Boot and/or Python backend development supporting AI services.
• Amazon Bedrock, OpenSearch vector search, embeddings, inference APIs, and enterprise AI deployment.
• Healthcare provider directory, referral workflows, practitioner, organization, healthcare service, and location data modelling.
• Secure API development using OAuth2, OpenID Connect, JWT, and enterprise authentication patterns.
• Cloud-native AWS development, monitoring, logging, CI/CD, and operational support.
• Strong analytical, problem solving, communication, and technical documentation skills.

Evaluation Criteria: 100 Points

• Enterprise AI development experience, including Retrieval Augmented Generation (RAG), Large Language Models (LLMs), semantic search, prompt engineering, AI agent development, Model Context Protocol (MCP), tool orchestration, and AI evaluation frameworks. 25 Points
• Healthcare interoperability experience, including FHIR R4/R4B, SMART on FHIR, Smile CDR, AWS HealthLake, REST APIs, Provider Registry, Master Data Management, healthcare terminology, and healthcare data integration. 25 Points
• Cloud application development experience, including Java/Spring Boot and/or Python, AWS cloud services, Amazon Bedrock, OpenSearch vector search, secure API development, CI/CD, monitoring, and scalable cloud-native architectures. 25 Points
• Experience working with digital health assets Hospital Report Manager (HRM), Enterprise Master Data Management, Consent Management Service, provincial identity services, and integration with Epic, Oracle Health (Cerner), MEDITECH, or other healthcare information systems. 25 Points

Deliverables:

• AI architecture, technical design documentation, and implementation plans supporting PHSD Referral Intelligence.
• AI agents capable of assisting users in identifying appropriate referral destinations using PHSD provider directory information.
• Retrieval Augmented Generation (RAG) pipelines utilizing PHSD, Smile CDR, AWS HealthLake, and other approved healthcare data sources.
• Model Context Protocol (MCP) servers exposing PHSD capabilities for AI-assisted applications.
• Semantic search implementation supporting provider, practitioner, organization, healthcare service, specialty, and location discovery.
• Vector embedding generation, indexing, retrieval optimization, and relevance tuning.
• AI services capable of validating referral destinations, identifying incomplete referral information, and recommending appropriate providers or healthcare services.
• Integration with PHSD FHIR APIs, Smile CDR, AWS HealthLake, Provider Registry, Master Data Management services, and other provincial digital health assets.
• Prompt libraries, orchestration workflows, tool definitions, and structured AI interaction patterns.
• AI evaluation framework including groundedness, retrieval quality, factual accuracy, hallucination detection, citation validation, and response quality metrics.
• Secure authentication and authorization integration supporting SMART on FHIR, OAuth2/OIDC, and role-based access controls.
• Operational dashboards, monitoring, telemetry, audit logging, and performance reporting for AI services.
• Unit testing, integration testing, AI evaluation testing, deployment automation, and CI/CD pipeline support.
• Technical documentation, operational procedures, AI governance documentation, knowledge transfer materials, and production implementation support.

Additional Terms

• The term of this Engagement Assignment is for 164 Business Days. The Engagement Assignment may be extended for unused Business Days at the Agency's discretion.
• The resource will comply with the Agency's policies and procedures.
• The resource will be issued an Agency laptop and is expected to provide at least one additional monitor, an external keyboard and a mouse at their own expense. In addition, when the resource is working from their home location they must have a private office space and are not permitted to work in an open communal space. Internet connection must be hard-wired and suitable bandwidth to support the IT requirements of this role. If these conditions cannot be met within their home office space, the resource will transition to full time in office, and the hybrid option will no longer be available.
• The Agency systems cannot be accessed from outside the province of Ontario, and Agency assets including laptops and related equipment cannot be removed from the province of Ontario, without prior written approval from the Agency.
• Assignment Type: This position is currently listed as "Hybrid". The resource under this request will be required to work onsite as per Hiring Manager sole discretion.