GenAI Forward Deployed Engineer IV

About the role

MINIMUM QUALIFICATIONS:

• Bachelor’s degree in Engineering, Computer Science, a related field, or

equivalent practical experience.

• 8 years of experience building and shipping production-grade AI-driven or

software solutions to external or internal customers using Python, C++,

TypeScript, or comparable languages.

• Experience leading technical discovery sessions with executive stakeholders

and engineering teams to define AI, media, and hardware infrastructure

requirements.

• Experience architecting and building scalable solutions with generative media

models and embedding them into cloud platforms, production workflows,

creative software suites, or pipelines.

• Experience architecting AI solutions that ensure data sovereignty, GDPR

compliance, and secure model governance/studio standards.

PREFERRED QUALIFICATIONS:

• Master’s or PhD in Computer Science, AI/ML, or Computer Graphics.
• Knowledge of diffusion models and autoregressive LLMs (including the

underlying Transformer architecture), training dynamics, hyperparameters, and

loss functions.

• Direct model fine-tuning (video, image, or audio), high-throughput and

inference on major cloud platforms, experience with flow matching, diffusion

transformers, or other advanced techniques.

• Professional experience in visual effects (VFX), gaming, or ad-tech

specialized as engineers in model, pipeline, or creative software suites,

with expertise in evaluation and output quality.

• Experience leading GenMedia creative vision, direct building synthetic data,

interactive apps, and high-fidelity assets that inspire clients and creators.

ABOUT THE JOB:

As a Forward Deployed Engineer (FDE) at Google Cloud, you are an embedded

builder who bridges the gap between frontier AI products and production-grade

reality within customers. Functioning as an "innovator-builder," you will move

beyond high-level architecture to code, debug, and jointly ship bespoke AI and

agentic solutions directly in the customer’s environment.

Designed for high-agency engineers with a founder’s mindset, you will manage

critical production blockers—including integration complexity, data readiness,

and state management. By embedding with strategic accounts, you will serve a

dual purpose: providing white-glove deployment of complex AI systems and acting

as a feedback loop, transforming real-world field insights into Google Cloud’s

future product roadmap.

Within Generative Media (GenMedia), you will specifically focus on embedding

Google's frontier multimodal models (video, image, audio) into production

reality across leading enterprises, platforms, and creative organizations.

It's an exciting time to join Google Cloud’s Go-To-Market team, leading the AI

revolution for businesses worldwide. You’ll excel by leveraging Google's brand

credibility—a legacy built on inventing foundational technologies and proven at

scale. We’ll provide you with the world's most advanced AI portfolio, including

frontier Gemini models, and the complete Vertex AI platform, helping you to

solve business problems. We’re a collaborative culture providing direct access

to DeepMind's engineering and research minds, empowering you to solve customer

challenges. Join us to be the catalyst for our mission, drive customer success,

and define the new cloud era—the market is yours.

Individual pay is determined by factors including job-related skills,

experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

• Develop complex AI applications, transitioning from prototypes to

production-grade agentic workflows.

• Architect the "connective tissue" between Google’s AI products and customer's

live infrastructure, including APIs, legacy data, and security perimeters.

• Build production-grade integrations, developer SDKs, and custom middleware

that wire Google’s AI media models directly into industry-standard creative

suites and secure studio environments.

• Identify repeatable patterns and friction points in Google’s AI stack,

converting them into reusable modules or formal product feature requests for

the Engineering teams.

• Co-build with customer engineering teams to instill Google-grade development

best practices, ensuring long-term project success and high end-user

adoption.