Overview
On Site
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - W2
Skills
Agentic AI
Vertex AI
GCP
Job Details
Senior AI Data Architect role, you should focus on these 5 high-impact skill clusters. These combine the "must-have" Google Cloud Platform 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.
2. Vertex AI & MLOps Lifecycle
Since this is a Google Cloud Platform-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.
Since this is a Google Cloud Platform-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).
3. Google Cloud Platform 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.
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 Google Cloud Platform.
4. 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.
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.
5. 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.
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.
Skill Google Cloud
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.