- 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: Sunnyvale, CA, USA; Cambridge, MA, USA; Kirkland, WA, USA; New York, NY, USA; Raleigh, NC, USA; Durham, NC, USA; Seattle, WA, USA; San Francisco, CA, USA.
Minimum qualifications:
- Bachelor's degree in Computer Science, a similar technical field, or equivalent practical experience.
- 5 years of experience in a technical role (e.g., software engineering, solutions consultant, etc.) or equivalent technical experience.
- 2 years of experience integrating or building production-grade generative AI, large language models (LLMs), or multi-agent workflows into applications.
- 1 year of experience producing engaging developer content (e.g., blogs, short-form videos, podcasts, live streams).
Preferred qualifications:
- Experience designing production-grade AI apps and agentic workflows to showcase secure, scalable deployments.
- Experience leading workshops and hackathons to foster a vibrant AI solution community on Google Cloud.
- Experience leading industry events while developing sample code and tutorials for strategic enablement.
- Proven ability of creating technical demos and content to demystify complex AI problems and drive developer adoption.
- Ability to lead pre-launch testing of AI features to provide actionable engineering feedback and resolve developer friction.
About the job
As a Cloud Developer Relations Engineer, you stand at the intersection of a technology movement shaping our world - between the people who build it and the customers who use it. Developer Relations Engineers are the engineering wing of Developer Relations. We ensure that Google Cloud and related open source projects like Kubernetes, Beam and TensorFlow are amazing for developers. As "customer zero" we're the first developers to use upcoming services and ensure they meet customer's needs. We provide feedback on API design, platform consistency and functionality. We write sample code and work with our technical writing teams to produce developer documentation, quickstarts and tutorials. We release open source code, participate in developer forums and help troubleshoot developer problems.
The Cloud Developer Relations team seeks a highly technical Developer Relations Engineer for the AI team. Our mission is to accelerate the developer journey from code to secure AI workloads in production. As a "builder-influencer," you will bridge developing and high-impact advocacy. You will build production-ready AI applications, integrate AI into secure product workflows, and demonstrate deployment at scale. Simultaneously, you will create engaging content, demos, blogs, and videos, that drives developer adoption to Google Cloud and Google AI.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $163000 - $236000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Be able to dogfood AI features and provide actionable feedback to developer teams to resolve developer friction and influence product roadmaps.
- Create engaging technical demos, blogs, and videos that demystify complex AI developer problems and drive share of voice.
- Manage developer programs, workshops, and hackathons to foster a vibrant community for AI solutions on Google Cloud.
- Develop comprehensive resources, including sample code and tutorials, while representing Google at industry events and conferences.
- Design, build, and maintain production-grade AI applications and agentic workflows to demonstrate deployment at scale.
