AI Data Architect with GCP

8 hours ago

Santa Ana, California, United States Talent Portus Full time

Job Description -

Role: Senior AI Data Architect with GCP experience.

Location: 4 days per week in Santa Ana, CA

Duration: 12+ months

All Visa Candidates area accepted

Job description

Senior AI Data Architect role, you should focus on these 5 high-impact skill clusters. These combine the "must-have" GCP technical stack with the emerging "Agentic" requirements that define this specific job.

  1. Agentic AI & Orchestration Frameworks

The JD specifically mentions Agentic AI and autonomous agents. Look for candidates who move beyond basic chatbots and can build systems that "think" and "act."

Key Keywords: Vertex AI Agent Builder, LangChain, LangGraph, CrewAI, AutoGen.

What to look for: Experience building multi-step workflows where an AI agent uses APIs (tools) to complete a task, rather than just generating text.

  1. Vertex AI & MLOps Lifecycle

Since this is a GCP-centric role, the candidate must be an expert in the Vertex AI suite. They need to demonstrate they can productionize models, not just build them.

Key Keywords: Vertex AI Pipelines, Model Registry, Feature Store, Model Monitoring, CI/CD for ML.

What to look for: Candidates who have experience with "Model Drift" detection and automated retraining pipelines (MLOps).

  1. GCP Data Lakehouse Architecture

The "Data" half of the title requires a deep understanding of how to store and process the massive datasets that fuel AI.

Key Keywords: BigQuery (specifically BigQuery ML and BigLake), Dataproc, Dataflow, Medallion Architecture (Bronze/Silver/Gold).

What to look for: Experience unifying "Data Lakes" (unstructured storage) with "Data Warehouses" (structured SQL) into a single Lakehouse on GCP.

  1. Generative AI & RAG (Retrieval-Augmented Generation)

The role requires architecting solutions using LLMs like Gemini. The candidate must understand how to "ground" these models in company-specific data.

Key Keywords: Gemini (Pro/Flash), Vector Databases (Vertex AI Search & Conversation), Prompt Engineering, Embeddings.

What to look for: Evidence of building RAG architectures where an LLM retrieves real-time data from a database to provide accurate, non-hallucinated answers.

  1. Cross-Functional Technical Leadership

At the 15+ year level, this person is a "Senior Visionary." They need to bridge the gap between business ROI and technical implementation.

Key Keywords: Reference Architectures, Stakeholder Management, Solution Blueprints, Cost Optimization (FinOps).

What to look for: Experience presenting to CXOs, mentoring data engineering teams, and performing "Vendor/Tool Evaluations" for GenAI.

Thanks and regards

Mohd Furquan/Rehan

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