[Hiring] Architect - Google Vertex AI & Databricks (Agentic AI Solutions) @NTT DATA

Role Description

This role involves designing and implementing advanced AI systems and architectures.

• Design end-to-end agentic AI systems integrating Vertex AI Agent Builder, Gemini models, and Databricks Mosaic AI Agent Framework.
• Develop hybrid architectures where Databricks is the governed data and tool plane, and Vertex AI is the reasoning/LLM runtime.
• Define patterns for RAG, tool calling, workflow orchestration, and multi-agent systems.
• Architect secure connectivity between Google Cloud and Databricks using IAM, service accounts, and workload identity federation.
• Architect AI/analytics systems using Delta Lake, Unity Catalog, Databricks SQL, MLflow, and Databricks Vector Search.
• Develop governed toolsets (SQL tools, Python functions, REST connectors) for agent use cases.
• Optimize pipelines using Delta Live Tables, streaming architectures, and feature/embedding stores.
• Implement and optimize Gemini 1.5/2.0/2.5 Pro, Flash, and Nano models on Vertex AI.
• Build production agents using Vertex AI Agent Builder with tool integrations, schema-based prompts, grounding, and observability.
• Leverage Model Garden, Model Armor, Evaluation, and Realtime Inference APIs for secure and compliant deployment.
• Build enterprise-grade agent-based systems with robust tool-use, grounding, error recovery, and structured outputs.
• Reference architectures for LLM-powered copilots, autonomous data/ops agents, customer support/search agents, and supply-chain or financial intelligence agents.
• Integrate RAG using vector stores, embedding pipelines, and multimodal grounding.
• Define CI/CD for AI workloads using MLflow, GitHub/GitLab, Cloud Build, or Azure DevOps.
• Implement observability dashboards for latency, tokens, tool calls, success rate, and hallucination metrics.
• Apply data/AI governance policies, lineage, and security using Unity Catalog, Vertex Model Armor, GCP IAM, and secrets management.
• Work with cross-functional teams (data engineering, cloud, infra, product) to deliver high-impact AI platforms.
• Mentor teams on generative AI, Databricks Lakehouse, GCP, and modern agentic paradigms.
• Translate business objectives into solution architectures and technical roadmaps.

Qualifications

• 10+ years of experience in Data Engineering / ML / Cloud Architecture.
• Expertise in Databricks (Delta Lake, DLT, SQL, UC, MLflow, Mosaic AI).
• Strong hands-on experience with Google Cloud (BigQuery, Vertex AI, Cloud Run, GCS, IAM).
• Experience building agentic AI systems with Vertex AI or Databricks Mosaic tools.
• Strong programming background in Python (LangChain/Agent frameworks optional but beneficial).
• Expertise in RAG pipelines, prompting, schema-based prompting, and retrieval optimization.
• Experience deploying and scaling AI solutions in production.