AI Data Engineer Jobs at Google with Visa Sponsorship
AI Data Engineer jobs at Google sit at the intersection of large-scale data infrastructure and machine learning systems, covering pipelines, feature engineering, and model deployment at significant scale. Google has a consistent track record of sponsoring work visas for this function, including H-1B visa, H-1B1 visa, and E-3 visa classifications.
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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.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
Our Frontier AI team exists to answer one question: "What’s next?" by building AI-native foundations that are trusted, flexible, and multimodal—making advanced intelligence as accessible as a SQL query.
As Senior Staff Software Engineer, you will define the technical trajectory and provide the architectural goal across Google Cloud Platform to realize the end-to-end foundations powering our autonomous agents.
The US base salary range for this full-time position is $262,000-$365,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Lead the technical discovery and implementation of agentic workflows that transform the Data Cloud into an autonomous, AI-native foundation.
- Mentor a high-caliber team of engineers to balance rapid prototyping with the rigorous technical validation required for frontier AI capabilities.
- Partner with co-innovation stakeholders to translate "frontier problems" into clear technical specs, ensuring AI agents can access precise context for high-quality business actions.
- Balance immediate prototyping needs with long-term research goals, prioritizing high-leverage experiments that prove the value of embedded foundation models like Gemini.
- Design and deploy multimodal analytics capabilities directly within the Data Cloud, making complex model reasoning as accessible and performant as a standard SQL query.
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 7 years of experience leading technical project strategy, ML design, and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 5 years of experience with design and architecture; and testing/launching software products.
- 2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 5 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
Benefits
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Kirkland, WA, USA; Seattle, WA, USA; Sunnyvale, CA, USA.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
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Get Access To All JobsTips for Finding AI Data Engineer Jobs at Google
Align your portfolio to Google's stack
Google's AI Data Engineer roles prioritize hands-on experience with distributed systems, BigQuery, Vertex AI, and TensorFlow. Structure your portfolio around end-to-end ML pipelines and large-scale data processing to match what their engineering teams are actively building.
Target roles listed under specific product teams
Google posts AI Data Engineer positions across Google Cloud, DeepMind, and Google Research. Applying to team-specific openings rather than generic postings signals a clearer fit and gets your application to hiring managers closer to the actual work.
Confirm your visa type before the offer stage
Google sponsors H-1B, H-1B1 visa, and E-3 visas. Knowing which classification applies to your nationality before final-round interviews helps you respond clearly when compensation and start-date conversations begin, avoiding delays in the offer process.
Prepare for H-1B cap timing if you're cap-subject
If you need a cap-subject H-1B, USCIS registration opens in March for an October 1 start date. Receiving an offer in Q4 or Q1 means you'll likely wait through a full lottery cycle, so negotiate start dates and interim work authorization options with your recruiter early.
Use Migrate Mate to filter verified AI Data Engineer openings
Identifying which Google roles are actively open to visa sponsorship takes real research. Use Migrate Mate to filter AI Data Engineer jobs at Google by visa type, so you're applying to roles where sponsorship is confirmed rather than assumed.
Request clarity on LCA filing and prevailing wage tier
Google files a Labor Condition Application with the DOL before your H-1B petition can proceed. Ask your recruiter which wage level the role is certified at, since Level I and Level II certifications can affect the offer structure and your petition's approvability.
Frequently Asked Questions
Does Google sponsor H-1B visas for AI Data Engineers?
Yes, Google sponsors H-1B visas for AI Data Engineer roles. They also sponsor H-1B1 visas for Chilean and Singaporean nationals and E-3 visas for Australian nationals. The specific classification depends on your citizenship. Google's legal and HR teams manage the petition process internally, so your recruiter will coordinate the filing once you have a confirmed offer.
Which visa types does Google commonly use for AI Data Engineer roles?
Google uses the H-1B for most international AI Data Engineers, the H-1B1 visa for Chilean and Singaporean nationals, and the E-3 exclusively for Australian citizens. AI Data Engineer roles qualify as specialty occupations under USCIS guidelines because they require at minimum a bachelor's degree in computer science, data engineering, or a closely related field.
How do I apply for AI Data Engineer jobs at Google?
Applications go through Google's careers portal at careers.google.com. Search for AI Data Engineer roles filtered by location and team. The process typically involves an initial recruiter screen, followed by technical phone interviews covering data systems and ML infrastructure, then a virtual on-site loop. You can also browse open, visa-sponsorship-confirmed AI Data Engineer positions at Google through Migrate Mate before applying directly.
What qualifications does Google expect for AI Data Engineer roles?
Google expects a bachelor's or master's degree in computer science, data engineering, or a related technical field. Beyond credentials, strong candidates demonstrate production-level experience with distributed data pipelines, proficiency in Python or SQL, and familiarity with ML workflow tooling. For more senior levels, prior work on feature stores, model serving infrastructure, or real-time data systems is a practical differentiator.
How do I plan my timeline if I need Google to sponsor my visa?
Timeline depends on your visa type. E-3 and H-1B1 visas have no annual cap and can be filed throughout the year, so start dates are more flexible. Cap-subject H-1B petitions require USCIS registration in March, with employment beginning no earlier than October 1. If you're cap-subject, factor in a six-to-twelve month gap between offer and start date, and confirm whether Google offers cap-gap or OPT extension support during that window.