Logicplanet, Inc.
Logicplanet, Inc.

Google Cloud Platform Architect

Hybrid in Dallas, TX, US • Posted 1 hour ago • Updated 1 hour ago
Contract Corp To Corp
Contract Independent
Contract W2
12 Months
No Travel Required
Able to Sponsor
Hybrid
Depends on Experience
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Artificial Intelligence
  • Cloud Computing
  • Extract, Transform, Load
  • Data Flow
  • Generative Artificial Intelligence (AI)
  • Incident Management
  • Machine Learning Operations (ML Ops)
  • Google Cloud Platform
  • PySpark
  • Python
  • IBM iSeries
  • ELT
  • Mainframe
  • Terraform
  • z/OS
  • Regulatory Compliance
  • Data Masking

Summary

Role : Google Cloud Platform Architect
Location: Dallas, Texas - Hybrid

 

Job Description

  • System Architecture: Architect the end-to-end design of a scalable, GenAI-powered remediation platform on Google Cloud Platform. Design ingestion patterns to normalize data from Mainframe (z/OS), AS400, and Splunk into a Common Information Model (CIM).
    BigQuery Data Foundation: Establish BigQuery as the centralized source of truth. Design and implement efficient ELT/ETL pipelines and utilize BigQuery Vector Search for RAG (Retrieval-Augmented Generation) workloads.
    Human-in-the-Loop (HITL) Workflow: Engineer the critical workflow for "Low Confidence" incident handling. Ensure seamless integration between AI-generated hypotheses and expert analyst resolution, creating closed-loop feedback mechanisms that improve model accuracy over time.
    Governance & Compliance: Implement row-level security (RLS) and data masking to meet Healthcare regulatory requirements while providing LLMs the context needed for inference.
    Model Lifecycle & MLOps: Oversee the LLM and MLOps lifecycle, managing retraining triggers based on verified analyst resolutions, model evaluation, and performance monitoring.
  • Technical Qualifications
    Cloud Platform: Expert-level proficiency in Google Cloud Platform (Vertex AI, BigQuery, Dataflow, Pub/Sub, Cloud Run, Cloud Functions).
    GenAI & RAG: Deep practical experience with RAG architectures, embedding models, and vector database management (specifically within the BigQuery ecosystem).
    Legacy Integration: Strong background in connecting legacy enterprise infrastructure (Mainframe/AS400) to modern cloud data pipelines.
    Engineering Practices: Proficiency in Python/SQL, PYSPARK and infrastructure-as-code (Terraform) for reproducible, automated deployment.
    Communication: Ability to serve as a technical bridge, explaining complex AI trade-offs to stakeholders while providing clear guidance to engineering teams

 

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10111282
  • Position Id: 8980152
  • Posted 1 hour ago
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