Assistant Vice President

As the Generative AI Architect, you will be the technical visionary responsible for the end‑to‑end design and delivery of generative AI systems (LLMs, diffusion models, multimodal transformers, etc.). You will work closely with managers, data scientists, data engineers, and business stakeholders to translate business needs into robust AI architectures, ensure scalability, security, and compliance, and champion best practices across the organization.

Responsibilities:

• Define the technical roadmap for generative AI capabilities aligned with product and business goals.
• Design, develop, and deploy AI/ML models and solutions focused on US healthcare datasets.
• Design high‑level system architectures (model training pipelines, serving infrastructure, data ingestion, monitoring, and governance).
• Lead the development, fine‑tuning, and optimization of large language models (LLMs), diffusion models, multimodal transformers, and related architectures
• Architect solutions for distributed training (e.g., DeepSpeed, ZeRO, FSDP) and inference at scale (GPU/TPU clusters, Kubernetes, serverless).
• Implement observability, logging, and automated alerting for model performance, drift, and resource utilization.
• Incorporate security best practices: model encryption, secure inference, access control, and compliance with GDPR, CCPA, HIPAA, etc
• Develop prototypes and proofs-of-concept using generative AI models and tools to solve complex problems.
• Support the evaluation, selection, and integration of AI technologies and frameworks in the healthcare domain.
• Collaborate with data engineers and analysts to create dashboards, visualizations, and reports to communicate AI outcomes to business stakeholders.
• Monitor model performance and retrain models as needed to ensure accuracy and reliability in production environments.
• Mentor junior engineers and share best practices on AI development, cloud deployment, and healthcare data handling.

Required Qualifications:

• Bachelor’s or higher degree in Computer Science, Engineering, Data Science, or a related technical field.
• 7+ years of experience designing and deploying AI/ML solutions
• Strong programming skills in Python, Scala, or similar languages used for AI development.
• Deep understanding of transformer architectures, attention mechanisms, and modern generative modeling techniques.
• Experience with generative AI models (e.g., GPT, BERT, or custom models) and machine learning frameworks like PyTorch, TensorFlow, or Hugging Face.
• Hands-on experience working with US healthcare data, including knowledge of healthcare standards (HL7, FHIR) and regulations (HIPAA).
• Experience with big data technologies (Spark, Delta Lake) and building data pipelines on Databricks.
• Proficient in SQL and data querying for healthcare datasets.
• Familiarity with cloud infrastructure, containerization (Docker, Kubernetes), and CI/CD pipelines for AI solutions.
• Strong analytical, problem-solving, and communication skills to work effectively with technical and non-technical stakeholders.