Software Developer - Artificial Intelligence (AI) - Senior

Software Developer - Artificial Intelligence (AI) - Senior 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. 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 DirectoriesExperience 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 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: 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 PointsHealthcare 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 PointsCloud 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 PointsExperience 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 Total: 100 Points Deliverables 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. Knowledge Transfer Details: The resource will ensure full knowledge transfer is provided to the Agency team before end of engagement. Some of this might occur at the end of the engagement but will also be shared as information is obtained/consolidated. Key deliverables will be shared with team.The resource must provide all related documentation as part of knowledge transfer protocol. Documents will be reviewed by the appropriate leads and signed off by manager/director.The resource will work collaboratively with the Agency team throughout the assignment and ensure key deliverables, milestones, and documentation are shared.A walkthrough of any demos, development, etc. will be required before the end of the engagement. Supplier Comments MSP Notes Shortlist Date: 2026-08-06, 2:00 p.m. 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 with Health Services DirectoriesExperience with AWS AI services including Amazon Bedrock and related AI services.Experience designing prompt orchestration, tool calling, and agent workflows.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 Location: Hybrid (onsite as needed) Public Sector Experience: must have # of submissions/supplier: 2 Job Type & Location This is a Contract position based out of Toronto, ON. Pay And Benefits The pay range for this position is $100.00 - $120.00/hr. Workplace Type This is a hybrid position in Toronto,ON. À propos de TEKsystems et TEKsystems Global Services Nous sommes un fournisseur de services aux entreprises et de technologies. Nous accélérons la transformation de nos clients. Notre compétence en stratégie, conception, exécution et opérations libère la valeur de l’entreprise par un éventail de solutions. Nous sommes une équipe de 80 000 personnes qui collaborent avec plus de 60 000 clients, notamment 80 % du Fortune 500 en Amérique du Nord, Europe et Asie, qui collaborent avec nous dans le cadre de nos capacités full-stack et notre rythme. Nous sommes des penseurs stratégiques, des collaborateurs pratiques qui aident les clients à exploiter le changement et maîtriser le dynamisme de la technologie. Nous bâtissons le futur en livrant les résultats et en créant un impact positif dans nos communautés mondiales. TEKsystems et TEKsystems Global Services sont des entreprises d’Allegis Group. Découvrez d’autres informations à TEKsystems.com. Ordonnance sur l’égalité des chances de San Francisco: Conformément à l’Ordonnance sur l’égalité des chances de San Francisco, pour tous les postes situés dans la ville et le comté de San Francisco, nous examinerons les candidatures des personnes qualifiées ayant un casier judiciaire ou des antécédents criminels. Utilisation de l’intelligence artificielle (IA): Nous pouvons utiliser l’intelligence artificielle (IA) pour soutenir certaines étapes de notre processus d’embauche, notamment la recherche, la présélection et l’évaluation des candidatures. L’IA aide à analyser les candidatures et les qualifications, mais les décisions finales sont prises par notre équipe de recrutement. En soumettant votre candidature, vous reconnaissez et acceptez que celle-ci puisse être examinée à l’aide d’outils d’IA. About TEKsystems And TEKsystems Global Services We’re a leading provider of business and technology services. We accelerate business transformation for our customers. Our expertise in strategy, design, execution and operations unlocks business value through a range of solutions. We’re a team of 80,000 strong, working with over 6,000 customers, including 80% of the Fortune 500 across North America, Europe and Asia, who partner with us for our scale, full-stack capabilities and speed. We’re strategic thinkers, hands-on collaborators, helping customers capitalize on change and master the momentum of technology. We’re building tomorrow by delivering business outcomes and making positive impacts in our global communities. TEKsystems and TEKsystems Global Services are Allegis Group companies. Learn more at TEKsystems.com. The company is an equal opportunity employer and will consider all applications without regard to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law. San Francisco Fair Chance Ordinance: Pursuant to the San Francisco Fair Chance Ordinance, for all positions located in the city and county of San Francisco, we will consider for employment qualified applicants with arrest and conviction records. Use of Artificial Intelligence (AI): We may use Artificial Intelligence (AI) to support parts of our hiring process, including sourcing, screening, and evaluating candidates. AI helps assess applications and qualifications, but final decisions are made by our hiring team. By applying, you acknowledge and agree that your application may be reviewed using AI tools.econnaissez et acceptez que celle-ci puisse être examinée à l’aide d’outils d’IA.