Job Summary

Domain Expert - MedTech AI & Digital Health. Role overview Field Detail Job title Practice Lead - MedTech AI & Digital Health Role type Domain Expert Reporting to DU Head/Delivery Manager Focus Medical Imaging AI, SaMD, Clinical GenAI, Regulatory Compliance. Role objective Lead the MedTech practice in building AI-enabled, regulation-ready medical devices and software, from imaging AI to agentic clinical and regulatory workflows.

Key responsibilities

- Strategy: Define the MedTech AI roadmap across imaging, monitoring, and point-of-care devices.
- Tech hubs: Lead three hubs: Imaging & Computer Vision, Clinical GenAI & Regulatory Intelligence, and Connected Devices & Interoperability.
- Compliance: Embed IEC 62304, ISO 13485, ISO 14971, and GMLP into AI delivery; support FDA 510(k) and EU MDR submissions.
- Standards: Own the medical AI 'Golden Stack' and MLOps practices for validation and traceability.
- Accelerators: Build reusable assets, such as regulatory compliance assistants and imaging AI components.
- Growth: Drive pre-sales solutioning, client advisory, and thought leadership.

Mandatory skills

- Experience: 15-20 years total; at least 8 years in MedTech, including 5+ in AI/ML architecture.
- Medical imaging and computer vision: Deep learning for medical images and video (PyTorch, OpenCV).
- Production AI deployment:



Model optimization and edge inference (ONNX Runtime, TensorRT, OpenVINO).
- Regulatory knowledge: IEC 62304, ISO 13485, ISO 14971, FDA 510(k).
- Healthcare standards: DICOM, PACS.
- Generative AI: LLMs, RAG, and agentic AI in production.
- Leadership: Led multi-disciplinary AI teams and senior client stakeholders.

Desired skills

- Clinical workflows: radiology, cardiology, obstetrics, ultrasound
- AI regulation: FDA AI/ML guidance, PCCP, EU MDR, EU AI Act, IEC 81001-5-1
- Interoperability: HL7 v2, FHIR, EHR integration
- MONAI, NVIDIA Clara/Holoscan, Orthanc
- Cloud healthcare services and MLOps (MLflow, Kubeflow)
- Publications, patents, or open-source work in medical AI

Tech stack expectations

- Area Technologies: Imaging AI PyTorch, MONAI, YOLO, MedSAM
- Inference: ONNX Runtime, TensorRT, OpenVINO
- GenAI: Llama, Mistral, GPT, Gemini, Claude; LangChain/LangGraph; vector DBs
- Platform: Python, C++, FastAPI, Docker, Kubernetes

Education and qualifications

Degree or diploma in CS, IT, Electronics, or related field, or equivalent experience.

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