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Software Engineer, Enterprise Product Strategy and Architecture

Job in Austin, Travis County, Texas, 78719, USA
Listing for: Google LLC
Full Time position
Listed on 2026-06-06
Job specializations:
  • Software Development
    AI Engineer, Data Engineer
Salary/Wage Range or Industry Benchmark: 207000 - 301000 USD Yearly USD 207000.00 301000.00 YEAR
Job Description & How to Apply Below
Position: Staff Software Engineer, Enterprise Product Strategy and Architecture
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Note:

By applying to this position you will have an opportunity to share your preferred working location from the following:
Austin, TX, USA;
New York, NY, USA;
San Jose, CA, USA.

Minimum qualifications:

* Bachelor's degree or equivalent practical experience.

* 8 years of experience in software development.

* 5 years of experience testing and launching software products.

* Experience designing and implementing large-scale data architecture frameworks, enterprise data warehouses/data lakes, or production-grade AI/ML pipelines.

Preferred qualifications:

* 10 years of experience in technology, software engineering, or enterprise architecture, with a heavy emphasis on data engineering or AI/ML systems.

* Experience influencing decentralized technical teams and drive the concrete adoption of centralized engineering standards without direct authority.

* Experience developing data and product strategies across a diverse portfolio of internal systems within a complex, large-scale enterprise.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile;

the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

In this role, you will be responsible for defining, driving, and scaling enterprise-wide architectural standards, reference models, and patterns that empower Corporate Engineering to build innovative, secure, and data-driven capabilities.

At Corp Eng, we build world-leading business solutions that scale a more helpful Google for everyone. As Google's IT organization, we provide end-to-end solutions for organizations across Google. We deliver the right tools, platforms, and experiences for all Googlers as they create more helpful products and services for everyone. In the simplest terms, we are Google for Googlers.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $301000 (USD) + 20% bonus target + bonus + equity + benefits

Learn more about benefits at Google.

Responsibilities

* Design, develop, and maintain enterprise-grade reference architectures, blueprints, and technical roadmaps for next-generation data platforms and AI/ML capabilities across Corporate Engineering.

* Conduct deep-dive technical design consultations and architecture reviews to ensure emerging product strategies align with long-term data scalability and enterprise AI safety goals.

* Support the Enterprise Architecture Board (EAB) by reviewing high-impact data and AI proposals, proactively identifying architectural fragmentation, and mitigating security threats or technical debt.

* Lead technical forums, architecture deep-dives, and workshops to elevate the data engineering and AI competencies of technical leads and builders across Corporate Engineering.

* Establish reusable architectural patterns, templates, and principles for data ingestion, pipeline orchestration, model deployment, and generative AI integrations to reduce systemic redundancy and accelerate delivery.
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