Applied AI Engineer

Overview We are seeking an experienced AI Engineer to design, develop, and deploy production-grade AI solutions that address operational challenges within healthcare-related environments. This role involves working closely with cross-functional teams, stakeholders, and end users to build scalable backend systems and AI-powered applications that integrate into real-world workflows. The ideal candidate combines strong software engineering fundamentals with hands-on experience delivering AI applications in production settings. This is a highly collaborative role focused on building practical, reliable systems rather than experimental research projects. Key Responsibilities Design, build, and maintain scalable backend services and APIs for AI-driven applicationsDevelop and deploy generative AI solutions that support operational and business workflowsIntegrate large language model (LLM) services and third-party APIs into production systemsArchitect and implement AI agents, automation pipelines, and intelligent workflow solutionsCollaborate with product, engineering, data, and operational teams to identify business problems and translate them into technical solutionsWork directly with stakeholders and users to ensure applications align with real-world processes and requirementsBuild secure, maintainable, and high-performance systems using modern backend development practicesParticipate in code reviews, sprint planning, testing, and ongoing system optimizationOwn projects end-to-end, from technical design and prototyping through deployment and supportRequired Qualifications 4-6+ years of experience in software engineering, backend engineering, solutions engineering, or a related technical roleProfessional experience building and maintaining production applications using PythonHands-on experience developing and deploying AI-powered applications in live environmentsStrong understanding of backend system architecture and API design principlesExperience building and consuming RESTful APIs and integrating external servicesFamiliarity with relational and/or NoSQL databasesAbility to work independently while collaborating effectively across technical and non-technical teamsStrong problem-solving, communication, and organizational skillsPreferred Experience Experience working with healthcare, laboratory, revenue cycle, supply chain, or operational data systemsFamiliarity with healthcare interoperability and data standards such as HL7 or FHIRExposure to LIS/LIMS platforms, claims processing systems, or healthcare workflow applicationsExperience working in startup or fast-paced product environmentsUnderstanding of scalable cloud infrastructure and deployment workflowsTechnical Skills & Tools: Core Technologies PythonFastAPI or similar backend frameworksSQLRESTful APIsLLM platforms and AI service integrationsAdditional Technologies KubernetesTerraformVector databasesCloud infrastructure and deployment toolingRelational and NoSQL database systemsWhat Success Looks Like Delivering reliable AI-enabled systems that solve operational challenges at scaleTranslating complex workflows into intuitive technical solutionsBuilding maintainable backend services that support high availability and performanceTaking ownership of critical systems and continuously improving them through iteration and collaborationDesired Skills and ExperienceOverviewWe are seeking an experienced AI Engineer to design, develop, and deploy production-grade AI solutions that address operational challenges within healthcare-related environments. This role involves working closely with cross-functional teams, stakeholders, and end users to build scalable backend systems and AI-powered applications that integrate into real-world workflows.The ideal candidate combines strong software engineering fundamentals with hands-on experience delivering AI applications in production settings. This is a highly collaborative role focused on building practical, reliable systems rather than experimental research projects.Key ResponsibilitiesDesign, build, and maintain scalable backend services and APIs for AI-driven applicationsDevelop and deploy generative AI solutions that support operational and business workflowsIntegrate large language model (LLM) services and third-party APIs into production systemsArchitect and implement AI agents, automation pipelines, and intelligent workflow solutionsCollaborate with product, engineering, data, and operational teams to identify business problems and translate them into technical solutionsWork directly with stakeholders and users to ensure applications align with real-world processes and requirementsBuild secure, maintainable, and high-performance systems using modern backend development practicesParticipate in code reviews, sprint planning, testing, and ongoing system optimizationOwn projects end-to-end, from technical design and prototyping through deployment and supportRequired Qualifications4-6+ years of experience in software engineering, backend engineering, solutions engineering, or a related technical roleProfessional experience building and maintaining production applications using PythonHands-on experience developing and deploying AI-powered applications in live environmentsStrong understanding of backend system architecture and API design principlesExperience building and consuming RESTful APIs and integrating external servicesFamiliarity with relational and/or NoSQL databasesAbility to work independently while collaborating effectively across technical and non-technical teamsStrong problem-solving, communication, and organizational skillsPreferred ExperienceExperience working with healthcare, laboratory, revenue cycle, supply chain, or operational data systemsFamiliarity with healthcare interoperability and data standards such as HL7 or FHIRExposure to LIS/LIMS platforms, claims processing systems, or healthcare workflow applicationsExperience working in startup or fast-paced product environmentsUnderstanding of scalable cloud infrastructure and deployment workflowsTechnical Skills & Tools:Core TechnologiesPythonFastAPI or similar backend frameworksSQLRESTful APIsLLM platforms and AI service integrationsAdditional TechnologiesKubernetesTerraformVector databasesCloud infrastructure and deployment toolingRelational and NoSQL database systemsWhat Success Looks LikeDelivering reliable AI-enabled systems that solve operational challenges at scaleTranslating complex workflows into intuitive technical solutionsBuilding maintainable backend services that support high availability and performanceTaking ownership of critical systems and continuously improving them through iteration and collaboration...