Google

Runs Search and YouTube and builds Gemini AI

Applied Solutions Architect - Data and AI

Implementation & Technical Account ManagementConfirmed live in the last 24 hours

Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

A bachelor's degree or equivalent practical experience.
10 years of experience with cloud-native architecture in a customer-facing or support role.
Experience with Big Data technologies or concepts, including analytics warehousing, data processing, data transformation, data governance, data migrations, extract, transform, load (ETL), extract, load, transform (ELT), SQL, NoSQL, performance or scalability optimizations, or batch versus streaming.
10 years of experience architecting and delivering large-scale distributed data platforms, cloud-native software, and AI-driven systems in a customer-facing engineering, principal architecture, or technical consulting role.
Experience designing property or knowledge graphs (GQL, Cypher, RDF/OWL), enterprise semantic catalogs, or multimodal data pipelines that process and index unstructured data alongside tabular data.
Real-world experience taking data and AI systems through enterprise information security and governance sign-off into production, implementing automated large language model/agent evaluation harnesses, semantic caching, and compute/query optimization for high-concurrency workloads.
A proven track record of owning multi-stakeholder technical transformations, quantifying architectural trade-offs, and building consensus with executives.

Responsibilities

Lead the design, development, and iterative refinement of data-centric and AI-powered solutions on Google Cloud Platform, demonstrating how data and AI address specific business needs.
Collaborate with customers to understand their business challenges, technical requirements, and strategic objectives.
Mentor and guide team members, fostering innovation and continuous learning.
Establish and promote best practices and methodologies for data-motivated solutions, and contribute to industry thought leadership through publications, presentations, and community engagement.
Lead end-to-end architectural design and engineering of next-generation agentic data platforms, unifying operational and analytical data estates, open multimodal lakehouses, semantic knowledge catalogs, and graph reasoning to ground and scale autonomous AI agents.
Drive solutions from initial architecture through enterprise security, governance, and production readiness, while shaping the strategic direction of reusable engineering assets.
Assist fellow sales Googlers by solving key technical issues for customers.
Liaise with product marketing management and engineering teams to stay informed about industry trends and devise enhancements to Google Cloud products.

Lead the design, development, and iterative refinement of data-centric and AI-powered solutions on Google Cloud Platform (GCP), showcasing the potential of data and AI to address specific business needs.
Collaborate closely with customers to understand their business challenges, technical requirements, and strategic objectives.
Mentor and guide team members, fostering a culture of innovation and continuous learning.
Establish and promote innovative best practices and methodologies for data-motivated solutions, actively contributing to industry thought leadership through publications, presentations, and community engagement.

Minimum qualifications:

Bachelor's degree or equivalent practical experience.
10 years of experience with cloud native architecture in a customer-facing or support role.
Experience with Big Data technologies or concepts, such as analytics warehousing, data processing, data transformation, data governance, data migrations, extract, transform, load (ETL), extract, load, transform (ELT), SQL, NoSQL, performance or scalability optimizations, or batch versus streaming.

Preferred qualifications:

10 years of experience architecting and delivering large-scale distributed data platforms, cloud-native software, and AI-driven systems in a customer-facing engineering, principal architecture, or technical consulting role.
Experience designing property/knowledge graphs (GQL, Cypher, RDF/OWL), enterprise semantic catalogs, or multimodal data pipelines that process and index unstructured data alongside tabular data.
Real-world experience taking data and AI systems through enterprise InfoSec and governance sign-off into production, implementing automated LLM/agent evaluation harnesses, semantic caching, and compute/query optimization for high-concurrency workloads.
Proven track record of owning multi-stakeholder technical transformations, quantifying architectural trade-offs and building consensus with executives.

When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.

The Google Forge Team partners with our most strategic customers to bring their transformative goals to life. In the agentic era, enterprise data architectures must evolve from passive Systems of Intelligence built for human-scale reporting into active, governed "Systems of Action" engineered for agent-scale autonomy.

In this role, you will lead the end-to-end architectural design and engineering of next-generation agentic data platforms—unifying operational and analytical data estates, open multimodal lakehouses, semantic knowledge catalogs, and graph reasoning to ground and scale autonomous AI agents. You will play a key leadership role in driving solutions from initial architecture through enterprise security, governance, and production readiness, while mentoring team members and shaping the strategic direction of our reusable engineering assets.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Bachelor's degree or equivalent practical experience.
10 years of experience with cloud native architecture in a customer-facing or support role.
Experience with Big Data technologies or concepts, such as analytics warehousing, data processing, data transformation, data governance, data migrations, extract, transform, load (ETL), extract, load, transform (ELT), SQL, NoSQL, performance or scalability optimizations, or batch versus streaming.

About the Company

Google

Runs Search and YouTube and builds Gemini AI

Google runs the world's most used search engine and free services such as YouTube, Android, and Gmail, and it builds the Gemini AI models that work inside them. In 2017, its researchers invented the transformer, the neural network design behind ChatGPT and most other AI chatbots. People use these services without paying, and Google earns most of its money from ads placed beside search results and YouTube videos. Businesses rent computing power and Gemini models through Google Cloud, and Google also sells subscriptions and Pixel phones. Larry Page and Sergey Brin founded Google in 1998 as Stanford PhD students; it is based in Mountain View, California, United States, and is the main business of parent company Alphabet.

Company size: 10,001+
Company stage: IPO
Headquarters: Mountain View, CA
Founded: 1998

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