Google Cloud Principal Architect - Gen3 EMR (AI & Cloud)

The Project We are embarking on an ambitious journey to redefine healthcare technology by building a "Gen3" Electronic Medical Record (EMR) system. Moving beyond traditional monolithic systems, this next-generation platform will be cloud-native, event-driven, and fundamentally infused with Generative AI to drastically reduce clinical burden and unlock unprecedented data insights.

The Role As the Principal Architect for the Gen3 EMR, you will act as the technical nucleus of the initiative. Your primary focus will be the rigorous discovery of existing application landscapes and defining the architectural blueprint for the new system. You will champion the integration of advanced AI workloads using an Anthropic/LangChain stack into a highly scalable microservices environment.

This is a highly visible leadership role requiring a balance of deep technical expertise in modern AI/Cloud architectures and exceptional communication skills to manage stakeholder expectations and produce definitive technical documentation.

Key Responsibilities Application Discovery & Strategic Roadmap (Primary Focus)

Lead comprehensive technical due diligence and application discovery phases to understand legacy workflows and data models.

Define the transition strategy from current state to a target "Gen3" state based on microservices, event-driven architecture (EDA), and serverless principles.

Create detailed architectural blueprints, system interaction diagrams (PlantUML), and whiteboards (Miro) to communicate the vision.

Design and act as the Technical Lead for the platform’s AI capabilities, moving beyond simple API calls to complex, stateful AI agents.

Architect solutions utilizing

Anthropic Claude

models tailored for clinical data processing.

Define the standards for LLM orchestration using

LangChain

and complex agentic flows using

LangGraph .

Implement robust observability, evaluation, and tracing for AI workflows using

LangSmith .

Design the retrieval architecture (RAG), integrating vector databases like

Qdrant

with relational data (PostgreSQL) for context‑aware AI outputs.

Core Architecture & Google Cloud Platform Cloud Leadership

Architect the infrastructure on

Google Cloud Platform , specifically focusing on GCP LZA Design, GCP Networking and Integration, Security and Governance.

Define the standards for a polyglot microservices backend, leveraging

Java

for core transactional services and

Python

for data/AI services.

Design high-throughput, asynchronous data backbones using

Apache Kafka

for real‑time event streaming across the EMR.

Technical Governance, Reporting & Communication

Serve as the primary technical point of contact for executive leadership and project stakeholders.

Translate complex architectural decisions into clear business value propositions through regular technical reporting.

Maintain rigorous technical documentation and architectural decision records (ADRs).

Technical Mentorship & Team Enablement

Provide high‑level guidance to

Frontend

teams, ensuring the React/TypeScript/Vite architecture aligns with backend APIs and AI capability exposure.

Steer

Backend

teams on service boundaries, API contracts, and data access patterns.

Drive the adoption of modern development tools, including AI‑assisted coding (Cursor, VS Code) to accelerate development velocity.

Qualifications Must‑Have Technical Experience

15+ years of software engineering experience

with 5+ years in a Principal or Chief Architect role handling enterprise‑scale distributed systems.

Proven track record in Application Discovery:

Experience analyzing legacy systems and defining modernization strategies for complex domains.

Deep GCP Expertise:

Demonstrable experience architecting cloud‑native solutions on Google Cloud, particularly GKE.

Production AI/LLM Experience:

Hands‑on experience architecting GenAI solutions using the

LangChain ecosystem

(LangChain, LangGraph, LangSmith) and integrating LLMs like

Claude .

Experience with vector databases such as

Qdrant , Pinecone, or Weaviate in a RAG context.

Strong background in event‑driven architecture using

Apache Kafka .

Expertise in designing polyglot microservices environments (Java and Python preferred).

Leadership & Communication Skills

Exceptional written and verbal communication skills, with the ability to switch fluently between deep technical discussions with engineers and strategic presentations to executives.

Demonstrated experience creating high‑quality architectural documentation (using tools like PlantUML, Miro, or similar).

Preferred Qualifications

Certifications:

Google Professional Cloud Architect (PCA) or Professional Cloud.

Experience with

Google Vertex AI

capabilities.

Understanding of "Agentic" workflows and autonomous AI agents.

Significant experience in Healthcare IT, specifically with EMR/EHR systems, HIPAA compliance, and standards like FHIR/HL7.

Familiarity with the modern frontend stack (React, TypeScript, React Query) to better guide frontend leads.

Experience establishing CI/CD pipelines (Jenkins) and QA automation strategies in a microservices environment.

Preferred Tech Stack

Frontend:

React, React Query, React Router, React Hook Form, TypeScript, HTML/JS/CSS, Vite, Webpack, Jest

Backend:

Java (Spring Boot), JUnit; Python, Pytest

Cloud / DevOps:

Google Cloud, Google Kubernetes Engine (GKE), Jenkins, Kafka

Database:

Qdrant (vector DB), PostgreSQL, Redis

QA Automation:

Cypress, Selenium, Apache JMeter, BrowserStack

Architecture patterns:

Microservices, Serverless, Event‑Driven Architecture (EDA)

Development / AI tools:

Cursor, VS Code, Claude, Spring Tool Suite, LangChain, LangGraph, LangSmith

Others:

Miro, PlantUML, GitHub

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