Lead AI Architect (Healthcare Domain)

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Experience:

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Role Definition

Principal Agentic AI Architect / Tech Lead

end-to-end technical vision and architecture

Project Aura

scalable, secure, and seamlessly integrated

PureHealth's technology stack

multi-agent AI systems, LLM orchestration, and RAG pipelines

clinical-grade, low-latency applications

Key Responsibilities

• Lead the technical vision and architecture for Project Aura, ensuring alignment with business goals.
• Evaluate, select, and implement AI frameworks, libraries, and orchestration tools (e.g., LangChain, LlamaIndex).
• Design multi-agent AI systems with robust inter-agent communication, task orchestration, and workflow management.
• Implement Retrieval-Augmented Generation (RAG) pipelines for efficient and contextually relevant AI outputs.
• Ensure scalable, secure, and maintainable architecture for low-latency clinical applications.
• Collaborate with product managers, data scientists, and software engineers to integrate AI systems with existing infrastructure.
• Mentor and guide AI engineering teams, fostering best practices in coding, system design, and deployment.
• Conduct technical reviews, define standards, and ensure high code quality, performance, and reliability.
  

Required Skills And Experience

• 10+ years of experience in AI system design, software engineering, and technology leadership.
• Deep expertise in multi-agent systems, LLM orchestration, and AI-driven workflows.
• Hands-on experience with frameworks such as LangChain, LlamaIndex, and other agentic AI architectures.
• Strong knowledge of RAG (Retrieval-Augmented Generation) pipelines and vector databases.
• Experience designing low-latency, clinical-grade applications or enterprise-grade AI systems.
• Proven track record of leading AI engineering teams and delivering complex projects.
• Proficiency in Python, PyTorch, TensorFlow, and AI/ML engineering tools.
• Strong understanding of software architecture, cloud platforms (AWS/Azure/GCP), containerization, and microservices.
• Excellent problem-solving, communication, and leadership skills.
  

Preferred Skills

• Exposure to HIPAA-compliant or healthcare-grade systems.
• Knowledge of vector search, embeddings, and semantic search architectures.
• Familiarity with prompt engineering, AI safety, and agentic system evaluation.
• Experience in full-stack AI system deployment in cloud or on-prem environments.