- Company Name
- Talent Portus
- Job Title
- AI Data Architect with GCP
- Job Description
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**Job Title:**
AI Data Architect with GCP
**Role Summary:**
Design, build, and operationalize end‑to‑end AI/ML solutions on Google Cloud Platform. Lead the integration of large language models, autonomous agent frameworks, and data lakehouse architectures to deliver production‑ready, cost‑effective intelligence products that support business objectives.
**Expectations:**
- Deliver on time and within budget for multi‑year AI strategy projects.
- Demonstrate strong stakeholder management, communicating technical plans to CXOs and cross‑functional teams.
- Mentor engineering teams, set technical standards, and drive continuous improvement of ML pipelines.
- Maintain rigorous governance: monitoring, drift detection, security, and compliance.
**Key Responsibilities:**
1. Architect and implement Vertex AI pipelines, Model Registry, Feature Store, and automated retraining workflows.
2. Build Agentic AI solutions using Vertex AI Agent Builder, LangChain/Graph, CrewAI, or AutoGen to create autonomous, multi‑step workflows that interact with APIs and tools.
3. Design and deploy a GCP Lakehouse, integrating BigQuery/BigLake, Dataflow, Dataproc, and Medallion (Bronze/Silver/Gold) layers to unify structured and unstructured data.
4. Develop Retrieval‑Augmented Generation (RAG) systems: generate embeddings, configure Vertex AI Search/Conversation, calibrate prompt engineering, and integrate Gemini LLMs for grounded, low‑hallucination responses.
5. Define reference architectures, evaluate vendors, manage FinOps, and present technology roadmaps to executive leadership.
6. Ensure robust monitoring (Model Drift, latency, SLA), security, and compliance across all components.
**Required Skills:**
- Deep expertise in GCP services: Vertex AI, BigQuery, BigLake, Dataflow, Dataproc, Cloud Storage.
- Proven experience with MLOps: CI/CD for ML, model versioning, automated retraining, deployment at scale.
- Hands‑on with Agentic AI frameworks: Vertex AI Agent Builder, LangChain, LangGraph, CrewAI, AutoGen.
- Strong knowledge of Large Language Models (Gemini, GPT‑family) and RAG architecture.
- Data lakehouse architecture: unifying lake and warehouse layers, medallion modeling, ingestion pipelines.
- Design & implementation of vector databases (Vertex AI Search, Vertex AI Conversation).
- Stakeholder communication, technical leadership, mentorship, FinOps‑aware cost optimization.
- Programming: Python, SQL, Kubernetes, Docker, and scripting for pipelines.
- Version control (Git), CI/CD platforms (Jenkins, GitHub Actions), and on‑prem or Cloud‑based build tools.
**Required Education & Certifications:**
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
- Minimum of 10–15 years of senior data architecture or ML engineering experience.
- GCP Professional Data Engineer or GCP Professional Machine Learning Engineer certification preferred.
- Additional certifications in Generative AI (e.g., Google Generative AI certification) or relevant vendor qualifications are a plus.