Description

You will lead the technical vision and architecture for agentic AI systems designed to automate medical record analysis and EHR updates.

Responsibilities

• Architect and implement agentic AI frameworks using LangChain, CrewAI, or custom multi-agent systems with MCP and A2A protocols.
• Integrate machine learning models for NLP of clinical notes, ICD-10 prediction, and severity assessment.
• Fine-tune transformer-based models and SLMs to optimize performance, cost, and latency.
• Ensure AI agent compliance with HIPAA and CMS guidelines while implementing bias mitigation and explainability.
• Lead pod-level sprints, mentor junior engineers, and coordinate system scalability across teams.
• Prototype and deploy agents in EHR environments, monitoring accuracy and manual intervention reduction.

Required Skills

• 8+ years of experience in AI engineering with 3+ years focused on agentic or autonomous AI systems.
• Expertise in fine-tuning models, SLMs, knowledge graphs, and transformer architecture.
• Experience with closed-source models (GPT series) and open-source models (Llama, BERT).
• Proficiency in Python, TensorFlow, and PyTorch.
• Hands-on experience with NLP libraries including spaCy and Hugging Face Transformers.
• Practical knowledge of MCP and A2A protocols for inter-agent communication.
• Cloud platform experience with AWS or Azure.
• Deep understanding of healthcare regulations including HIPAA and CMS guidelines.
• Master's or PhD in Computer Science, AI, or a related field.

Preferred Skills

• Experience with EHR integrations such as Epic or Cerner.
• Knowledge of medical ontologies like SNOMED CT.

Key Skills

Education

Bachelor's or Master's degrees