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NTT DATA Logo NTT DATA · IT - Software Development

Agentic AI Systems Developer

Canada, Toronto · Job Posted May 03, 2026
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Job Description

You will design and build agentic AI systems for healthcare using the NeuroStack Agentic Operating System. You will work closely with clinical SMEs, healthcare operations experts, and compliance teams to deliver production-grade AI solutions across diagnostics, care coordination, clinical documentation, population health, and operational optimization. This role blends Generative AI, classical ML, and full-stack engineering in regulated environments.

Job Responsibility

  • Design and implement agent-based AI workflows for healthcare use cases (clinical assistants, triage agents, care pathway optimization, RCM automation)
  • Build LLM-powered systems (RAG, tool-calling agents, multi-agent orchestration)
  • Develop classical ML models (risk scoring, prediction, clustering, anomaly detection)
  • Implement HIPAA aware AI architectures with auditability and traceability
  • Build full-stack applications (Python APIs, AI services, UI dashboards)
  • Integrate with EHRs, data lakes, and healthcare systems (FHIR/HL7 exposure preferred)
  • Collaborate with SMEs to translate medical workflows into agent logic
  • Deploy, monitor, and optimize AI systems in Azure

Requirements

  • 8–12+ years (AI/ML, Software Engineering)
  • Strong experience in Python-based AI systems
  • Hands-on experience with GenAI (LLMs, RAG, embeddings, prompt engineering)
  • Experience with traditional ML (classification, regression, NLP, time-series)
  • Full-stack experience (API design + UI integration)
  • Azure cloud experience (Azure ML, Azure OpenAI, Functions, AKS)
  • Experience working in regulated or compliance-heavy domains
  • Comfortable working with subject-matter experts
  • Strong learning mindset and adaptability
  • Experience building production AI systems, not just prototypes
  • Ability to explain AI decisions to non-technical stakeholders
  • Interest in agentic AI and next-generation AI architectures

Nice to have

  • Healthcare domain exposure
  • FHIR / HL7 familiarity
  • AWS, GCP, or NVIDIA AI stack experience
  • Knowledge of model governance and explainability
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