JD Below
Senior AI Solution Architectrole, 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.
- Agentic AI & Orchestration Frameworks
The JD specifically mentionsAgentic AIandautonomous 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.
- Vertex AI & MLOps Lifecycle
Since this is a GCP-centric role, the candidate must be an expert in theVertex AIsuite. 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).
- 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.
- Generative AI & RAG (Retrieval-Augmented Generation)
The role requires architecting solutions using LLMs likeGemini. 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.
- Cross-Functional Technical Leadership
At the 1015+ 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.