Senior Specialist, Full Stack AI Engineer

About Amplify HealthWho We AreAmplify Health Asia Pte. Limited (Amplify Health) is a pan-Asian health technology and analytics company which brings together health technology assets, proprietary data analytics and healthcare expertise to support innovation across the healthcare value chain.Headquartered in Singapore, Amplify Health operates in 10 markets across the region: Australia, Hong Kong, India, Indonesia, Malaysia, New Zealand, the Philippines, Singapore, Thailand and Vietnam.Amplify Health develops integrated solutions that empower healthcare payors, providers and policymakers across Asia to identify value and drive new partnerships, understand variation and address systemic inefficiencies—with the aim of improving outcomes for individuals and the sustainability of health systems.Powered by a clinically enriched data foundation, Amplify Health’s health intelligence platform combines modular AI solutions, context-aware automation and deep regional insights to offer localised, AI-powered health solutions spanning health payment integrity to chronic disease management. The company’s technology has earned recognition at several industry competitions, including the Celent Model Insurer Awards, ITC Asia Awards and SBR Technology Excellence Awards.As an ISO27001 certified organisation, Amplify Health maintains clearly defined policies, structured oversight mechanisms and ongoing risk assessments that ensure alignment with global best practices on enterprise data securityOur Vision and Ambition To build the leading healthcare AI and platform services company in Asia that transforms the delivery of health and wellness for patients and communities by combining and leveraging the distinctive and complementary assets and strengths of AIA and Discovery.Amplify Health will simplify access to health data and AI Innovation to accelerate distinct and disruptive healthcare value insights and resulting improvements in health outcomes through value-based care, personalised care plans and aligning individuals’ lifestyle/ behavioural choices.By 2028, Amplify Health will have in place one of Asia’s strongest health-tech and AI capabilities; a comprehensive, integrated health technology stack supported by precision insights derived from proprietary data pools.The Position Summary The Full Stack AI Engineer is a senior member of Amplify Health’s Technology team, responsible for designing, building and operating secure, production-grade applications within Claims Pro. Claims Pro supports the end-to-end claims value chain, from provider management and eligibility through claims adjudication and payment, through configurable, white-label B2B capabilities that can be adapted to customer and market requirements across Asia, supporting payers, providers, employers and members. The role combines strong full-stack engineering with practical AI delivery, building React and TypeScript front ends in an Nx/Vite workspace, Java/Spring Boot services, REST APIs and PostgreSQL-backed data layers, while integrating enterprise AI services, LLM APIs, retrieval-augmented generation, intelligent document processing and responsible AI controls into relevant claims workflows. Working closely with Product, Design, architecture, data, DevOps, security and business stakeholders, the successful candidate will translate regulated business and operational requirements and high-value AI opportunities into reliable, scalable, secure, auditable and measurable software capabilities, supporting API-first integrations, healthcare and payer data interoperability, and reliable claims workflows across customers and markets. Responsibilities 1) Build Full-Stack AI-Enabled Products Design, build, and deploy full-stack AI-enabled applications for Claims Pro using React, TypeScript, Nx and Vite for responsive front-end experiences, and Java/Spring Boot services for secure back-end APIs, workflow integrations and production deployments, supporting configurable capabilities across provider management, eligibility, claims adjudication and payment in line with agreed product requirements. Develop intuitive user interfaces, dashboards, conversational experiences, and document-based workflows that embed AI capabilities into real business processes while maintaining accessibility, performance and usability standards. Build scalable back-end services, API-first REST APIs, integration layers and PostgreSQL-backed data access patterns using SQL, JPA/Hibernate, JDBC and Flyway to connect AI services and Claims Pro workflows with payer, provider and healthcare systems, using HL7 FHIR and SMART on FHIR interoperability and secure access patterns where applicable. Partner with Product, Design, business stakeholders, and engineering teams to translate claims business and operational requirements and relevant AI opportunities into useful, trusted, secure and measurable product features that can be configured for customer and market needs. 2) Design and Develop Generative AI, RAG & Agentic Solutions Design, develop, and deploy AI applications using enterprise foundation models and AI services such as OpenAI, Azure OpenAI, Gemini, Claude or equivalent platforms. Build RAG solutions using embeddings, vector search, semantic search, enterprise knowledge sources, secure retrieval patterns, evaluation controls and auditable data access. Develop AI agents, copilots, chatbots, and intelligent automation flows that support user productivity, decision support and operational efficiency within governed product workflows. Engineer prompts, orchestration patterns, evaluation frameworks and guardrails to improve model quality, reliability, traceability, safety and business relevance. 3) Implement Intelligent Document Processing & AI Services Develop document processing solutions using OCR, Azure Document Intelligence, and other AI services to extract, classify, validate, and transform structured and unstructured information. Design human-in-the-loop review, feedback, and validation workflows to improve accuracy, explainability, auditability and user trust in AI outputs. Integrate AI capabilities such as language understanding, vision, speech, translation, content moderation and analytics into product and business applications where relevant. Design secure healthcare and payer data pipelines, schema migrations, validation and data-quality controls, and monitoring patterns to support AI retrieval, analytics, quality measurement and continuous improvement, including bulk data processing and near-real-time claims workflows where required by product requirements. 4) Deliver Production-Grade Engineering, Cloud Operations & Governance Move AI use cases from prototype to production through robust software engineering practices, including automated testing with Jest/Testing Library and JUnit/Spring Boot testing, code review, CI/CD, release management, monitoring, logging and operational support, embedding privacy, security, performance and observability into development and testing. Design secure, scalable and cost-effective cloud-native architectures on Azure or other cloud environments, considering cloud-agnostic service design where appropriate, with observability, performance, latency, configuration, dependency and cost controls to support reliable Claims Pro services and integrations. Implement OAuth2/OIDC-based authentication and authorization, secure APIs, sensitive-data handling, Responsible AI, privacy-by-design, auditability, compliance and governance controls suitable for healthcare, financial and insurance systems, aligned with applicable market regulations and secure exchange of healthcare and payer data. Monitor application and AI solution quality, reliability, hallucination risk, model performance, user feedback and business impact; support post-launch monitoring, incident resolution and continuous improvement of Claims Pro applications and mission-critical B2B integrations based on evidence. 5) Drive Innovation, Technical Leadership & Cross-Functional Enablement Identify, assess, and prioritize high-value AI opportunities in partnership with Product, business, data, security, architecture, DevOps and engineering stakeholders. Provide technical recommendations on AI architecture, full-stack engineering patterns, cloud services, security controls, model selection, tooling and build-versus-buy decisions. Conduct targeted POCs and pilots with a clear path to production, including success metrics, adoption considerations, operational readiness, scaling plans and risk controls. Mentor engineers and stay current with advancements in full-stack engineering, GenAI, multimodal AI, agentic AI, LLM frameworks and healthcare technology trends, translating relevant developments into practical business value. Candidate Profile Experience and Qualifications B.E./B.Tech/MCA or equivalent qualification in Computer Science, Information Technology, Software Engineering, Artificial Intelligence, Data Science, or a related field. 7+ years of hands-on software engineering experience, including substantial end-to-end ownership of production full-stack applications across front-end, back-end, APIs, data layers, cloud services and operations. 2+ years of practical experience building AI, GenAI, LLM, RAG, intelligent automation or data-driven applications, preferably in enterprise or regulated environments. Advanced proficiency in TypeScript and React, including component architecture, routing, state management, forms, schema validation, frontend performance and accessibility, with hands-on experience in Nx and Vite preferred. Strong Java and Spring Boot experience building secure REST services, with practical knowledge of validation, exception handling, OpenAPI documentation and service-layer design. Strong PostgreSQL and SQL skills, including experience with JPA/Hibernate, JDBC, schema migrations, transaction management and query optimisation. Hands-on experience integrating AI capabilities into user-facing products, workflows, dashboards, conversational interfaces, document-processing journeys or operational tools. Practical experience with foundation models and enterprise AI services such as OpenAI, Azure OpenAI, Gemini, Claude or equivalent platforms. Experience implementing RAG solutions using embeddings, vector search, semantic search, enterprise knowledge sources, and appropriate retrieval and evaluation patterns. Experience moving software or AI solutions from prototype to production using engineering practices such as automated testing, code review, Git, CI/CD, monitoring, logging, release management and operational support. Experience with OAuth2/OIDC-based authentication and authorization, secure coding, API integration and common application security practices. Required: hands-on experience in financial services, insurance, healthcare or other regulated data environments, with a strong understanding of sensitive data, security, auditability and operational controls. Preferred: experience with health insurance claims workflows, provider management, eligibility, adjudication or payment, and healthcare or payer system integrations, including HL7 FHIR and SMART on FHIR where applicable. Ability to collaborate effectively with Product, Design, business, data, security, DevOps and engineering stakeholders, translating business needs into pragmatic, reliable and measurable technical solutions. Competencies & Core Characteristics: We are seeking a senior Full Stack AI Engineer who is a strong production software engineer first, with the practical AI delivery experience needed to embed GenAI, RAG, intelligent document processing, evaluation, guardrails and responsible AI capabilities into secure Claims Pro applications and healthcare and insurance workflows. Technical Domain Expertise Possesses deep full-stack engineering capability across React, TypeScript, Java/Spring Boot, REST APIs, PostgreSQL, cloud-native services, automated testing, CI/CD and production operations, with practical expertise in GenAI, LLMs, RAG, AI agents, intelligent document processing, evaluation and responsible AI engineering. Strategic Architect Able to design scalable, secure and maintainable full-stack AI solutions for configurable Claims Pro capabilities aligned with business objectives and regulated-domain requirements. Balances innovation with pragmatic implementation considerations including user experience, API-first design, healthcare and payer interoperability, data architecture, cost, performance, privacy-by-design, auditability, governance, maintainability and operational readiness across customers and markets. Unifier & Cross-Functional Influencer Collaborates effectively across Product, Design, engineering, architecture, data, security, DevOps, operations and business teams. Influences stakeholders through technical credibility, communicates complex full-stack and AI concepts clearly, and helps align solution choices with product value, delivery feasibility and responsible-use controls. Data-Driven Decisiveness Uses quantitative metrics, experimentation, model and retrieval evaluations, observability signals, production telemetry and operational insights to guide decisions. Continuously measures product quality, AI output reliability, hallucination risk, user adoption, performance and business impact, and drives improvements based on evidence. Customer-Obsessed Advocate Maintains a strong focus on delivering meaningful customer, user and business impact through Claims Pro. Designs configurable AI-enabled claims experiences and reliable payer and provider integrations that address customer and market requirements, improving productivity, accuracy, decision support, workflow efficiency and value realization while preserving trust, transparency and responsible use. Resilient Operator Thrives in rapidly evolving technology environments and adapts quickly to changing priorities. Demonstrates end-to-end ownership, accountability and persistence across design, implementation, testing, release, monitoring, incident response and continuous improvement of complex full-stack and AI-enabled systems. Insatiable Curiosity Continuously explores emerging full-stack engineering practices, cloud-native services, AI models, RAG patterns, agentic workflows, evaluation techniques and responsible AI controls. Challenges conventional approaches and actively identifies practical opportunities for innovation, automation and competitive advantage. Preferred Technical Skills Matrix Must Have Production full-stack software engineering across front end, back end, APIs, data layer and operations React, TypeScript, component architecture, routing, state management, forms, schema validation, accessibility and frontend performance Nx and Vite workspace development, reusable library boundaries, npm dependency management and modern frontend build practices Java, Spring Boot, REST APIs, OpenAPI documentation, validation, exception handling and service-layer design PostgreSQL, SQL, JPA/Hibernate, JDBC, Flyway, schema migrations, transaction management and query optimisation OAuth2/OIDC authentication and authorization, Auth0-style patterns, secure API design, secure coding and sensitive-data handling Automated testing, code review and quality gates using Jest/Testing Library, JUnit/Spring Boot testing or equivalent tools Git, npm, Gradle, CI/CD, release automation, monitoring, logging, observability and production support LLM API and enterprise AI service integration, including OpenAI, Azure OpenAI or equivalent foundation model platforms RAG architecture, embeddings, vector search, semantic search, secure retrieval, retrieval evaluation and enterprise knowledge integration AI application integration into user-facing products, dashboards, conversational interfaces, document workflows and operational tools Responsible AI, data privacy, application security, auditability, governance, prompt/data handling controls and model-output risk management Financial services, insurance, healthcare or other regulated data environment experience Good to Have Azure cloud-native services including Azure AI Foundry, Azure AI Search, Azure Document Intelligence, Azure Functions, App Services, Container Apps, Storage and Key Vault AWS or GCP cloud-native architecture, managed services, observability, performance engineering and cost-aware production operations Docker, Jib, Kubernetes or other container orchestration platforms for packaging, deployment and operational readiness Google Gemini, Anthropic Claude or other foundation model platforms beyond OpenAI/Azure OpenAI LangChain, LangGraph, Semantic Kernel, LlamaIndex, AutoGen or equivalent LLM orchestration and agent frameworks AI agents, copilots, agentic workflows, tool-using AI systems and workflow automation patterns OCR, intelligent document processing, extraction/classification pipelines and human-in-the-loop validation workflows MLOps, LLMOps, model evaluation, AI observability, prompt/version management, experimentation and production monitoring practices Knowledge graphs, graph-based retrieval, ontology design and enterprise knowledge management platforms Multimodal AI capabilities including vision, speech, translation, video, content moderation and document understanding Power Platform AI integration, workflow automation and low-code/no-code enablement for business users Domain experience with health insurance, claims, provider management, care management, healthcare analytics or other data-intensive financial products HL7 FHIR, SMART on FHIR, healthcare and payer system interoperability, and secure API-first integration patterns Bulk data processing and near-real-time integration patterns for healthcare, payer and claims workflows Join Us If you are passionate about leveraging data to drive healthier outcomes across Asia and thrive in a dynamic, mission-driven environment, we encourage you to apply. Amplify Health is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.