Google Cloud Solution Architect

Vation Digital Pvt. Ltd.; Bengaluru; On-site; INR 1,800,000 - 2,500,000; Full time

Benefits offered by this job

Competitive salary

Hybrid work model

Professional development opportunities

Job summary

A consulting firm in Bengaluru is seeking an experienced Google Cloud Solution Architect with expertise in Google AI and Data stack. The ideal candidate will architect and implement intelligent AI systems on Google Cloud, specializing in Generative AI and Agentic AI solutions. Key responsibilities include designing AI architectures, managing data pipelines, and providing technical leadership. This role requires 10+ years of experience in cloud environments, advanced skills in Python, and relevant AI certifications. The position offers a hybrid work model.

Qualifications

• 10+ years overall experience, with 4+ years in Google Cloud (GCP) and 2+ years in Google AI ecosystem.
• Proven experience as a Google Cloud Solution Architect, focused on AI/ML workloads.
• Strong programming background in Python.

Responsibilities

• Architect solutions for autonomous AI systems using LLMs and APIs.
• Design and implement Retrieval-Augmented Generation pipelines.
• Act as a trusted AI advisor to clients, translating business problems into AI-driven architectures.

Skills

Generative AI / LLMs

Agentic AI

BigQuery

Dataflow

Python

ML Ops

Education

Professional Cloud Architect certification

Professional Machine Learning Engineer certification

Tools

Vertex AI

LangChain

Google Generative AI SDKs

Job description

Hybrid, with primary location as Bangalore

Experience Level

10+ years overall experience, with 4+ years in Google Cloud (GCP) and 2+ years in Google AI ecosystem, including hands‑on Agentic AI and Generative AI solution development.

Role Overview

We are seeking an experienced Google Cloud Solution Architect with deep expertise across Google AI and Data stack, including Vertex AI, Generative AI, Agentic AI, and RAG architectures. The ideal candidate will design, implement, and scale intelligent, autonomous AI systems and data‑driven solutions on Google Cloud — integrating LLMs, APIs, and enterprise data to deliver measurable business value.

Key Responsibilities

AI & Agentic Solution Architecture

• Architect Agentic AI systems that combine LLMs, tools, APIs, and contextual reasoning to perform multi‑step, autonomous tasks.
• Design and implement Retrieval‑Augmented Generation (RAG) pipelines using Vertex AI Search, Vector Databases (Vertex Matching Engine / Pinecone / FAISS), and enterprise data sources.
• Develop Generative AI solutions leveraging Gemini models, Vertex AI Studio, and Model Garden.
• Integrate AI Agents with workflow automation, APIs, and enterprise applications (e.g., CRM, ERP, ServiceNow, custom APIs).

Model Lifecycle Management

• Fine‑tune and optimize foundation models using Vertex AI for domain‑specific use cases.
• Implement Explainable AI, continuous model monitoring, and ML Ops best practices using Vertex AI Pipelines and Cloud Build.
• Design and operationalize scalable, production‑ready AI environments in alignment with GCP architecture standards.

Data & Integration Layer

• Architect and manage data pipelines using Dataflow, Dataproc, Pub/sub, and BigQuery for ingesting and processing structured and unstructured data.
• Enable AI‑ready data ecosystems with well‑structured feature stores, metadata tracking, and embedding stores.
• Build APIs and integration layers for real‑time data access to enhance agentic decision‑making.

Advisory & Leadership

• Act as a trusted AI advisor to clients, translating business problems into AI‑driven architectures.
• Evaluate new Google AI capabilities (Gemini, Vertex AI Search, Grounding APIs, etc.) and recommend their use in enterprise contexts.
• Provide technical leadership and mentor engineering teams in modern AI design patterns.

Required Skills & Experience

• Proven experience as a Google Cloud Solution Architect, focused on AI/ML workloads.
• Deep hands‑on experience with
• Generative AI / LLMs (prompt engineering, embeddings, fine‑tuning)
• Agentic AI (orchestrating autonomous agents with tool use, memory, and planning)
• BigQuery, Dataflow, Pub/sub, Looker
• Strong programming background in Python, with experience using LangChain, Vertex AI SDK, or Google Generative AI SDKs.
• Familiarity with model orchestration, function calling, and memory‑enabled AI agents.
  Understanding of AI safety, governance, and grounding principles in enterprise applications.
• Professional Cloud Architect or Professional Machine Learning Engineer

Nice‑to‑Have

• Experience building multi‑agent systems or autonomous AI workflows (e.g., CrewAI, AutoGen, LangGraph).
• Exposure to Google Grounding APIs, Search and Conversation APIs, or custom tool integration in Vertex AI.
• Experience designing voice or chat‑based AI agents using Dialogflow CX or custom LLM frameworks.
• Familiarity with MLOps, CI/CD, and DataOps practices.

Soft Skills

• Strong communication, client engagement, and presentation skills.
• Ability to translate complex AI concepts into business outcomes.
• Self‑driven and continuously exploring cutting‑edge AI innovations.