AI Application Architect

Philips
China
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 3+ yearsSkills: ["Communication","Documentation","Collaboration","Problem-solving"]

Develop, integrate, test, and maintain a production-grade AI R&D QMS Harness for controlled medical-device AI workflows. Build prompt and retrieval pipelines, RAG services, workflow orchestration, evidence generation, and reviewer-facing outputs. Create governed AI agents for requirement-quality, traceability, compliance checks, and defect/change impact analysis, including audit logging, access control, observability, and OQ/PQ validation support. Partner with SMEs, QA, RA, and validation teams to expand use cases and maintain documentation.

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FursaFursa
Philips
Philips
2 months ago

AI Application Architect

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Source: Company careers pageValidated by: Fursa AI
Last checked: 27 days agoStatus: Live

Job Summary

Develop, integrate, test, and maintain a production-grade AI R&D QMS Harness for controlled medical-device AI workflows. Build prompt and retrieval pipelines, RAG services, workflow orchestration, evidence generation, and reviewer-facing outputs. Create governed AI agents for requirement-quality, traceability, compliance checks, and defect/change impact analysis, including audit logging, access control, observability, and OQ/PQ validation support. Partner with SMEs, QA, RA, and validation teams to expand use cases and maintain documentation.
Location: China
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Develop AI/LLM application services for a controlled AI Harness, including prompt pipelines, RAG services, workflow orchestration, evidence generation, and reviewer-facing outputs.
  • •Build read-only integrations to enterprise systems such as DOORS, ALM, ClearQuest, Windchill, SOP/document repositories, and DHF repositories.
  • •Implement AI agents for requirement-quality checks, traceability gap detection, DHF completeness review, defect/change impact analysis, compliance checks, and draft evidence generation.
  • •Create and maintain prompt libraries, retrieval pipelines, metadata schemas, source-citation mechanisms, and output templates aligned with approved QMS workflows.
  • •Support controlled deployment by implementing audit logging, model routing, access control, project isolation, evidence packaging, and performance/reliability/observability improvements.

Key Requirements

  • •3+ years of experience in software engineering and/or AI application development, including LLM integration or enterprise systems integration.
  • •Strong Python programming skills with practical experience building API-based backend services and structured data processing.
  • •Hands-on experience building RAG pipelines, prompt-based applications, evaluation workflows, or agent-style systems.
  • •Experience with vector search concepts such as document chunking, metadata filtering, citation generation, and prompt/version management.
  • •Familiarity with good engineering practices for logging, testing, reproducibility, access control, and deployment in controlled environments.
Experience:3+ yearsAI application developmentEnterprise systems integrationLLM integrationWorkflow automationMedical-device R&D
Skills:CommunicationDocumentationCollaborationProblem-solving
Tech Stack:PythonAPIsBackend servicesLLMRAGPrompt pipelinesVector searchDocument chunkingMetadata filteringCitation generationWorkflow orchestrationAudit loggingAccess controlObservabilityRetrieval pipelinesModel routingEvaluation workflowsPrompt regression testsCloud AI platformsModel APIs

Company Brief

Philips
Global health technology company focusing on diagnostic imaging, patient monitoring, and consumer health products. Philips develops medical devices, healthcare informatics, and solutions to improve patient care and personal well-being.
Industry: HealthTech
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Amsterdam, Netherlands
Founded: 1891
Glassdoor
Glassdoor: 3.8
WebsiteLinkedIn