Principal AI Architect

GE Healthcare GE Healthcare · Healthcare · Bengaluru, Karnātaka, India · Digital Technology / IT

GE HealthCare is seeking an AI Architect to design the foundation and strategy for their Gen AI program. This role involves architecting scalable AI models and systems, defining technical roadmaps, and overseeing the deployment and MLOps/LLMOps for generative AI solutions, including RAG patterns and fine-tuning. The architect will also ensure governance, security, and ethical AI practices, mentoring a team and staying updated on advancements. Experience with cloud platforms, AI/ML frameworks, and specific Generative AI tools is required, with a preference for healthcare industry experience and knowledge of regulations.

What you'd actually do

  1. Develop and maintain the foundational architecture for generative AI initiatives, ensuring scalability, security, and efficiency.
  2. Define the technical roadmap for generative AI capabilities, aligning with business objectives and CDO technology strategies.
  3. Define, deploy, and advance processes for: AI/ML development, MLOps, LLMOPs, and the monitoring, observability, security, and maintainability of AI models.
  4. Design and implement the infrastructure required to support generative AI models, including cloud-based solutions, data pipelines, and data storage platforms.
  5. Mentor a team of engineers and data scientists in the development and deployment of generative AI models.

Skills

Required

  • 4+ years of experience in designing and implementing AI architectures, with a focus on generative models (e.g., GPT, VAEs, GANs).
  • 10+ years of experience with cloud platforms (AWS preferred) and AI/ML frameworks (TensorFlow, PyTorch).
  • Experience with Generative AI RAG pattern and LLM fine tuning.
  • Experience with ML and Generative AI tools such as Amazon SageMaker and Amazon Bedrock.
  • Knowledge of ethical principles in AI development and deployment, including fairness, accountability, and transparency, ability to identify and address biases in data and models and understanding of techniques for interpreting and explaining AI models.
  • Proficiency in programming languages such as Python, R, Java, and C++ or related modern programming languages.
  • Deep understanding of machine learning algorithms, natural language processing, and deep learning techniques.
  • In-depth knowledge of CNNs, RNNs, LSTMs, Transformers, and their applications.
  • Strong understanding of NLP techniques, including text preprocessing, tokenization, stemming, lemmatization, sentiment analysis, and named entity recognition.
  • Excellent problem-solving skills and ability to work in a fast-paced, dynamic environment.
  • Strong communication and collaboration skills, with the ability to effectively convey complex technical concepts to non-technical stakeholders.

Nice to have

  • Master’s or PhD is a plus.
  • Experience with MLOps and CI/CD pipelines for AI model deployment.
  • Experience with AWS services such as SageMaker, Bedrock, EMR, S3, OpenSearch Service, Step Functions, Lambda, and EC2
  • Familiarity with ethical AI practices and AI governance frameworks.
  • Experience in the healthcare industry or with healthcare data is desirable.

What the JD emphasized

  • Generative AI RAG pattern and LLM fine tuning
  • ethical and responsible use of AI technologies
  • ethical principles in AI development and deployment, including fairness, accountability, and transparency
  • In depth understanding of healthcare regulations (HIPAA, GDPR, etc.), data privacy, and patient safety standards.

Other signals

  • designing, developing, and deploying generative AI solutions
  • architecting scalable AI models and systems
  • Define, deploy, and advance processes for: AI/ML development, MLOps, LLMOPs, and the monitoring, observability, security, and maintainability of AI models.