RQ00735 - Software Developer - Artificial Intelligence (AI) - Senior
About the role
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 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 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
Requirements 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.
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 Directories Experience 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
About Maarut
Maarut Inc is a company that is committed to working with clients' resources, culture, and capabilities in producing an overall strategic plan and product for their information technology system. We believe that by offering cost-effective software solutions to help meet changing business demands, businesses can sustain growth and help protect existing technology investments.
We are willing to work with clients both as one-stop vendor as well as open to integrate different components
As a full-service consulting firm, we can handle all aspects of your software project — specification, design, implementation, testing, and related services.
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RQ00735 - Software Developer - Artificial Intelligence (AI) - Senior
About the role
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 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 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
Requirements 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.
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 Directories Experience 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
About Maarut
Maarut Inc is a company that is committed to working with clients' resources, culture, and capabilities in producing an overall strategic plan and product for their information technology system. We believe that by offering cost-effective software solutions to help meet changing business demands, businesses can sustain growth and help protect existing technology investments.
We are willing to work with clients both as one-stop vendor as well as open to integrate different components
As a full-service consulting firm, we can handle all aspects of your software project — specification, design, implementation, testing, and related services.