C
Senior architect - AI, Medical Imaging & Digital Health Solutioning
Search Jobs
Search by job, company or skills
Search by job, company or skills
This job is no longer accepting applications
Medical Devices & Life Sciences | Bangalore, India / Hybrid
Exp - 15 - 18 years
Strong understanding of Medical Imaging and Healthcare IT ecosystems.
Experience with PACS, RIS, Enterprise Imaging, or Imaging Informatics platforms.
Knowledge of DICOM, HL7, FHIR, and healthcare interoperability frameworks.
Familiarity with Digital Pathology, Radiology, Cardiology, Oncology, or Diagnostic Imaging workflows.
Understanding of Digital Health, Connected Care, and Medical Device ecosystems.
Experience with Generative AI, LLMs, RAG, AI Agents, and Agentic AI solutions.
Knowledge of Machine Learning, Computer Vision, Imaging AI, and predictive analytics.
Understanding of AI platform ecosystems, MLOps, and AI governance practices.
Experience identifying and translating business opportunities into AI-powered solutions.
Job ID: 151429795
Skills:
Machine Learning, Nlp, Ai, AIML models, algorithms/processes, Deep learning development, Machine learning model
Skills:
process mining , Ibm Watson, Cloud, MLops, multi-agent orchestration, Claude, Business Process Mapping, Responsible AI frameworks, LLM architecture, Azure AI Copilot, IT enterprise architecture concepts, GenAI architecture, Google Vertex AI, observability, API-first, AI architecture, prompt engineering, agentic workflows, RAG, cloud AI platforms, MCP, AI governance, Amazon Bedrock, Gemini
Skills:
bedrock , Tensorflow, Pytorch, Python, AWS, SageMaker, Large Language Model, generative AI, Hugging Face Transformers, AI Architect, Retrieval Augmented Generation
Skills:
bedrock , Tensorflow, Pytorch, Python, AWS, SageMaker, Large Language Model, Hugging Face Transformers, generative AI, AI Architect, Retrieval Augmented Generation
Skills:
data engineering , Microservices, Ml, automation, Predictive Analytics, Devops, MLops, AWS, Azure, Computer Vision, Apis, Nlp, IaC, Ai, GenAI, hybrid environments, cloud-native, observability practices, data lakes, GenAI tools
