Enterprise AI Architect

Key Responsibilities

• Work with business and technical teams to identify functional requirements that drive smart healthcare technology solutions to meet growing organization needs
• Lead the Architecture, design and implementation of Traditional AI, Gen AI and Agentic AI solutions capable of clinical and operational intelligence and decision making, autonomous reasoning and contextual understanding
• Architect and design agentic AI solutions to orchestrate LLM powered multi-agent workflows including RAG enhanced retrieval from multimodal data
• Build supervised and unsupervised models, prompt and context engineering solutions and integrate LLMs into modern web and mobile applications which allow feedback and reinforcement learning
• Implement MLOps pipelines for continuous training, monitoring bias/fairness without compromising on quality, performance and uptime
• Develop and maintain model governance frameworks addressing explainability, bias mitigation and compliance with healthcare data regulations
• Mine and analyze data from internal/external data sets to methodically optimize operations across various departments including intake, clinical, revenue cycle and other operations
• Perform data/error analysis to continuously improve models, clean and validate data for uniformity and accuracy
• Stay ahead of emerging AI trends and research to continuously refine architectural best practices
• Mentor and coach other technical team members on the ethical use of AI, AI architecture design patterns

Qualifications

• At least 10+ years of proven experience primarily architecting AI/ML systems in productions environments
• 10+ years of experience in both supervised and unsupervised learning, statistics and neural network design
• 7+ years of experience building highly scalable mission critical enterprise grade AI applications at scale
• 5+ years of experience building mission critical health care applications, preferably in home health
• Hands-on experience with LLM’s generative AI frameworks such as Langchain, HuggingFace, OpenAI and Anthropic APIs and Transformer based architectures
• Proven experience with machine learning frameworks such as TensorFlow/Keras, PyTorch and Pandas
• Proven experience with classical data analysis such as Classification, Regression, Clustering and deep learning models such as RNN, CNN, GAN
• Proven experience with various data and AI related services in AWS (Bedrock, Textract, SageMaker, Comprehend)
• Proven experience building scalable solutions leveraging Docker, Kubernetes, AWS ECS
• Expert level knowledge of Python, R
• Proficiency with at-least two scripting languages (e.g. JavaScript, Python, Lua), SQL, No- SQL Databases
• Strong verbal and written communication skills
• Extremely strong analytical and problem-solving abilities