Senior Data AI Solution Architect

5 - 10 years

15 - 30 Lacs

Posted:4 weeks ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Senior Data & AI Solution Architect

Seeking a Senior Data & AI Solution Architect to design and implement a modern, scalable, and secure data and AI platform. The role involves building hybrid cloud architectures, enabling advanced AI/agent workflows, and supporting supply chain and logistics domains through intelligent, data-driven solutions.

Key Responsibilities

  • Architect and build secure, scalable data platforms on

    Google Cloud Platform

    , integrating structured, unstructured, IoT, and streaming data sources.
  • Design and manage

    enterprise Data Lakes

    , ensuring performance, governance, and interoperability.
  • Implement

    Master Data Management (MDM)

    frameworks for consistent, high-quality data across supply chain and operational systems.
  • Define infrastructure architecture across on-prem and cloud for scalable data & AI workloads.
  • Develop modular APIs and services for AI model integration, intelligent agents, and analytics.
  • Build architecture patterns leveraging

    agentic workflows

    , MCP, RAG pipelines, and LLM integration.
  • Establish strong governance, security, privacy, lineage, and observability frameworks.
  • Drive reliability, high availability, DR, and performance tuning across the platform.
  • Collaborate with supply chain, IoT, data engineering, and ML teams to prioritize and deliver platform capabilities.
  • Mentor teams and influence enterprise-wide standards for GCP-, MCP-, and agent-driven architecture.

Required Qualifications

  • 68 years in data architecture, distributed systems, or ML platform engineering.
  • Hands-on experience with GCP services:

    BigQuery, Vertex AI, Dataflow, Pub/Sub, Data Lakes, Looker

    .
  • Experience with

    IoT data

    , real-time analytics, and streaming pipelines.
  • Expertise in

    MDM, data quality, and stewardship

    .
  • Strong cloud/hybrid infrastructure knowledge, networking, Terraform, Kubernetes, CI/CD.
  • Understanding of

    LLMs, embeddings, RAG, and agent frameworks

    .
  • Proficiency in

    Python, Go, or Java

    , with microservices/API engineering skills.

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