4 hours ago

Distinguished Engineer, AI & Developer Experiences

Google

On Site
Full Time
$450,000
Seattle, WA

Job Overview

Job TitleDistinguished Engineer, AI & Developer Experiences
Job TypeFull Time
CategoryCommerce
Experience5 Years
DegreeMaster
Offered Salary$450,000
LocationSeattle, WA

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Job Description

About The Job

Google Cloud is seeking an experienced and visionary Principal or Distinguished Engineer to join our Developer Tools & Experiences team, covering groundbreaking developer tools.

In this pivotal role, you will not just be a builder of tools, but a technical leader who deeply understands the capabilities and trajectory of AI models. You will advise a team of engineers to define the technical strategy for how developers interact with AI, determining specifically where we can depend on model capabilities versus where we need to build tools to augment them. You will inform and influence how to approach the training of models as well as product innovation, ensuring our developer surfaces evolve in lock-step with the underlying model advancements.

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.

The US base salary range for this full-time position is $349,000-$485,000 + 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

  • Help define the technical vision and roadmap for Cloud’s developer tools (CLI, IDEs, Antigravity), aligning with the trajectory of our foundational models and anticipating the market and new models.
  • Drive the "AI for Developers" strategy by making critical technical decisions on when to "teach" the model through training versus when to create external tools for the model to call.
  • Facilitate a mindset shift within the team to prioritize model expertise, ensuring engineers understand how to build for stochastic model behaviors alongside deterministic code.
  • Drive the architecture, design, and implementation of highly scalable developer experiences, ensuring they are robust, performant, and secure.
  • Partner closely with product management, research, and executive leadership (reporting directly to VPs/GMs) to translate model capabilities into actionable engineering initiatives.

Minimum Qualifications

  • Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
  • 18 years of software engineering experience building and working with large-scale systems.
  • Experience in building, scaling, and training/fine-tuning AI models and systems.
  • Experience delivering large-scale developer tools or platforms.

Preferred Qualifications

  • Master's degree or Ph.D. in Computer Science, Engineering, or a related technical field.
  • Experience training Large Language Models (LLMs) or similar AI systems, with the ability to distinguish between problems solvable by training vs. tooling.
  • Experience working with foundational developer tools (CLIs, IDEs, SDKs) and a deep empathy for the developer workflow.
  • Deep understanding of model architectures and their limitations.
  • Strong understanding of industry trends, specifically regarding the capabilities of models.
  • Credibility as an engineering leader who can influence across a large team.

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 (statutory, where applicable); 5 days/event (discretionary)
  • Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
  • Baby Bonding Leave: 18 weeks
  • Holidays: 13 paid days per year

Key skills/competency

  • AI Strategy
  • Developer Tools
  • Technical Leadership
  • Large-Scale Systems
  • AI Model Training
  • System Architecture
  • Product Innovation
  • Executive Partnership
  • LLMs
  • Cloud Computing

Tags:

Distinguished Engineer, AI & Developer Experiences
AI strategy
developer tools
technical leadership
large-scale systems
model training
architecture
product innovation
executive partnership
market anticipation
vision definition
AI models
LLMs
cloud developer tools
CLIs
IDEs
SDKs
system design
scalable experiences
foundational models
stochastic models

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How to Get Hired at Google

  • Research Google's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
  • Tailor your resume: Customize your resume to highlight experience in AI, large-scale systems, and developer tools, aligning with the Distinguished Engineer, AI & Developer Experiences role requirements.
  • Showcase leadership and impact: Provide concrete examples of driving technical vision, influencing teams, and delivering large-scale products in your application.
  • Prepare for technical deep dives: Brush up on AI model architectures, large language models, cloud developer tools, and system design for Google's rigorous interviews.
  • Demonstrate strategic thinking: Be ready to discuss industry trends in AI, distinguishing between model capabilities and tooling needs, and influencing product direction.

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