AI/ML Solution Architect-Google Cloud Platform&Generative AI

StoneGate-Technologies LLC
3 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Remote

Tech stack

Java
Artificial Intelligence
Computer Programming
Continuous Integration
Distributed Systems
Identity and Access Management
Python
Software Architecture
Cloud Services
Google Cloud Platform
Fast Healthcare Interoperability Resources
Large Language Models
Prompt Engineering
Generative AI
AI Platforms
Kubernetes
Google Cloud Functions
Health Level Seven International
Machine Learning Operations
Api Gateway
Data Pipelines

Requirements

We re seeking a Senior AI/ML Solution Architect with deep expertise in Google Cloud Platform (Google Cloud Platform) and Generative AI to lead architecture, design, and delivery of nextgeneration AI solutions for a major healthcare client. This role requires handson technical leadership, strong solution design skills, and the ability to guide enterprisescale AI/ML initiatives., Prior experience delivering AI/ML or cloud solutions for healthcare clients (mandatory) Architecture & Engineering

  • Software Architecture for largescale, distributed systems

  • Endtoend AI/ML solution design, including data pipelines, model deployment, and MLOps Google Cloud Platform (Google Cloud Platform)

  • Strong handson experience with:

  • Vertex AI

  • Dialogflow / Dialogflow CX

  • Agent Development Kit (ADK)

  • Google Cloud Platform compute, storage, networking, IAM, API Gateway, Cloud Functions, Pub/Sub Generative AI & LLMs

  • Designing and implementing solutions using Large Language Models (LLMs)

  • Prompt engineering, finetuning, retrievalaugmented generation (RAG)

  • Conversational AI and agentbased architectures Programming

  • Proficiency in Python, Java, or Go

  • Strong engineering fundamentals and ability to build productiongrade AI services

Nice to Have

  • Experience with HIPAAcompliant architectures
  • Knowledge of FHIR, HL7, or other healthcare data standards
  • MLOps frameworks (Kubeflow, MLflow, CI/CD pipelines)

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