Senior Data Architect

Key Responsibilities
• End-to-End Architecture: Design GenAI-ready data infrastructure on GCP including data ingestion (Dataflow, Pub/Sub), BigQuery storage, vector search platforms (Vertex AI Matching Engine, Pinecone, FAISS), and feature storage.
• Vertex AI Systems: Lead deployment of pipelines, model training, versioning, CI/CD, experiment tracking, monitoring, and optimization using Vertex AI Pipelines, Matching Engine, Model Monitoring, and Explainable AI.
• Generative AI & Agentic Frameworks: Evaluate and integrate models such as PaLM/Gemini, LLMs, GANs, diffusion models; implement agentic AI constructs via LangChain, AutoGen, CrewAI, MetaGPT or ADK.
• MLOps / LLMops: Implement IaC workflows (Terraform or Cloud Deployment Manager), design LLM lifecycle pipelines, manage model drift, scaling, continuous fine-tuning and production observability