Agentic AI Architect(Multi Agent building on healthcare applications) is must

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Agentic AI Architect(Multi Agent building on healthcare applications) is must
Location: 100% remote in the US
Experience : 12 - 15+

MUST HAVES:

Must have prior G AI Architecture experience. Lumeris is in the process of moving from AWS to Google Cloud Platform - and the manager does not have any AI Architects on the team who have prior Google Cloud Platform experience.
Architect will be very 'hands-on' with architecture, coding support, guidance -- NOT looking for an Architect who is only involved in the strategy/vision and not willing to dive into the code when needed.

*Overview*

We are seeking an AI Architect specializing in Google Cloud Platform (Google Cloud Platform), with deep experience in advanced AI agents, agentic AI systems, and cutting-edge AI tech stacks, tailored to the challenges and opportunities within the Health Tech sector. This role is instrumental in designing and delivering robust, compliant, and innovative AI-powered solutions for healthcare applications, leveraging Google Cloud Platform services and agent frameworks to drive clinical, operational, and patient-centered transformation.

This position offers an exciting opportunity to pioneer agentic AI and next-generation intelligent systems for the health tech domain. You will help transform patient experiences, clinical workflows, and healthcare delivery through advanced Google Cloud Platform-powered solutions.

*Key Responsibilities*

Architect Advanced Health AI Solutions: Design, implement, and optimize compliant, scalable, and efficient AI systems on Google Cloud Platform for health tech use cases, utilizing Google Cloud Platform technologies like Vertex AI, BigQuery, Dataflow, and Looker to support clinical analytics, decision support, and workflow automation.
AI Agent Expertise in Healthcare: Build and lead autonomous AI agents capable of supporting diagnosis, predictive analytics, personalized medicine, interoperability, and patient engagement using state-of-the-art LLMs and multi-agent architectures.
Agentic AI Solution Delivery in Health Tech: Develop multi-node, agentic AI models to power healthcare applications (e.g., retrieval augmented generation for literature synthesis, semantic search in medical records, state graphs/agentic memory for patient histories, API orchestration across EHR and imaging systems).
Innovate with New AI Tech Stacks: Employ modern AI libraries and frameworks (LangChain, LangGraph, Hugging Face) and integrate with cloud-native platforms, vector databases, and health data standards (FHIR, HL7).
Cross-Functional Collaboration: As a leader in the data science team, engage with clinical, Product, IT, and business teams to scope requirements and deliver AI solutions aligned with healthcare objectives, regulatory standards, and patient safety priorities.
Operationalize Healthcare AI/ML Models: Lead the deployment and monitoring of production-grade healthcare AI and ML models on Google Cloud Platform, validating clinical performance, reliability, and security.
Research & Thought Leadership in Health AI: Stay ahead of emerging methodologies (agentic AI, generative AI, reinforcement learning) and prototype novel health applications including clinical decision support, patient risk stratification, and population health management.
Mentorship & Best Practices: Mentor teams on AI model governance, health data privacy and security (HIPAA, GDPR), and ethical frameworks for AI in health; champion best practices in operational excellence and continuous improvement.

*Required Qualifications*

Master s in computer science, AI, Machine Learning, Health Informatics, Engineering, or related field.
5+ years architecting AI/ML solutions; 2+ years building agentic AI or multi-agent systems, ideally with healthcare applications.
Deep expertise in Google Cloud Platform services: BigQuery, Vertex AI, Dataflow, Cloud Functions, and automation tools; experience integrating with health data ecosystems (EHR, HL7/FHIR).
Demonstrated ability developing autonomous agents/frameworks using LLMs and agentic methodologies (LangChain, LangGraph, OpenAI API), applied to clinical/nursing, operational, or administrative workflows.
Strong programming skills in Python; proficiency with AI/ML libraries (PyTorch, TensorFlow, Hugging Face); experience with health data analytics and interoperability.
Track record building enterprise-grade, AI-driven healthcare products that deliver actionable insights, automation, and improved patient outcomes.
Familiarity with reinforcement learning, multi-agent workflows, agent memory/state management, and safety/guardrails in healthcare contexts.
Google Cloud Platform Professional Cloud Architect and relevant AI/ML/Health Informatics certifications preferred.
Outstanding problem-solving, documentation, presentation, and stakeholder engagement skills.

*Desired Competencies*
Healthcare domain experience (clinical, analytics, R&D, or operational).
Experience developing and implementing GenAI or LLM-powered health applications (clinical summarization, coding, workflow automation).
Familiarity with advanced pipeline orchestration, backend services, and deployment strategies (Terraform, Docker, Kubernetes).
Strong understanding of healthcare privacy, security, compliance, and regulatory frameworks (HIPAA, GDPR, ISO 27001).
Passion for continuous learning and driving innovation in disruptive AI for healthcare.