GenAI Forward Deployed Engineer IV, GenMedia, Google Cloud

Google•San Diego, CA

28d•$207,000 - $300,000

About The Position

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.

Requirements

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.

Nice To Haves

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.

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.