Forward Deployed Engineer I, GenAI, Google Cloud
Google · Addison, TX
- On site
- Full-time
- $145,000 / year
- Addison, TX
Job highlights
- Build production-grade GenAI solutions.
- Integrate AI products with customer infrastructure.
- Develop evaluation and observability frameworks.
- Provide feedback to product engineering.
- Collaborate with customer engineering teams.
About the role
About the Job
As a Generative AI Forward Deployed Engineer (FDE) at Google Cloud, you will be an embedded builder who bridges the gap between frontier AI products and production-grade reality within customer environments. You will function as an innovator-builder, moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment. You will address blockers to production, including solving the integration complexities, data readiness issues, and state-management issues that prevent AI from reaching enterprise-grade maturity and by embedding with accounts, you will serve a dual purpose, providing white-glove deployment of AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap. 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.Responsibilities
- Serve as a developer for AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, Model Context Protocol (MCP) servers) that drive measurable Return on Investment (ROI).
- Architect and engineer the "connective tissue" linking Google’s AI products to customers' live infrastructure, including APIs, legacy data silos, and security perimeters as part of an expert team.
- Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency.
- Identify recurring field patterns and friction points across Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.
- Collaborate with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.
Key skills/competency
- Generative AI
- Google Cloud Platform
- Python
- Typescript
- Applied AI
- Production-grade AI solutions
- Agentic solutions
- Cloud Platform
- Multi-agent systems
- AI optimization
Skills & topics
- Forward Deployed Engineer
- GenAI
- Google Cloud
- AI Engineer
- Machine Learning Engineer
- Python
- Typescript
- Cloud Computing
- Generative AI
- Large Language Models
- LLM
- Vertex AI
- Gemini Models
- Production AI
- Agentic Systems
- Multi-agent Systems
- Cloud Platform
- Software Engineer
- AI Solutions
How to get hired
- Tailor your resume: Highlight experience with Python, Typescript, applied AI, and cloud platforms.
- Showcase AI projects: Detail your work on production-grade AI-driven solutions and pre-trained models.
- Demonstrate cloud expertise: Emphasize your experience architecting or deploying on Google Cloud Platform.
- Prepare for technical interviews: Be ready to discuss AI concepts and coding challenges.
Technical preparation
Practice building AI solutions with Python.,Familiarize with Google Cloud services.,Study prompt engineering and RAG techniques.,Understand multi-agent system frameworks.
Behavioral questions
Describe a complex AI integration challenge.,How do you handle production blockers?,Share an experience providing customer feedback.,How do you collaborate with engineering teams?
Frequently asked questions
- What are the minimum qualifications for a Forward Deployed Engineer GenAI at Google Cloud?
- The minimum qualifications include a Bachelor's degree in Science, Technology, Engineering, or Mathematics, or equivalent practical experience. You'll also need experience building and shipping production-grade AI-driven solutions using Python or Typescript, applied AI with a focus on pre-trained models, and experience architecting or deploying on a Cloud Platform like Google Cloud Platform.
- What is the salary range for this Forward Deployed Engineer GenAI role at Google?
- The US base salary range for this full-time position is $102,000-$145,000, plus bonus, equity, and benefits. The exact salary will depend on factors like your work location, skills, experience, and education.
- What are the preferred qualifications for the Forward Deployed Engineer GenAI position?
- Preferred qualifications include a Master’s degree or PhD in AI, Computer Science, or a related technical field. Experience implementing multi-agent systems using frameworks like LangGraph or CrewAI, and knowledge of "LLM-native" metrics and optimization techniques are also highly preferred.
- Can I work remotely for this Forward Deployed Engineer GenAI role at Google?
- This role offers flexibility in working locations across various US cities, including San Francisco, CA; Atlanta, GA; Austin, TX; and Seattle, WA, among others. While not explicitly stated as remote, the wide range of location options suggests a hybrid or flexible arrangement might be possible depending on the specific team and business needs.
- What kind of AI projects will I be working on as a Forward Deployed Engineer GenAI at Google Cloud?
- As an FDE, you'll be an embedded builder creating production-grade agentic solutions within customer environments. This involves coding, debugging, and shipping bespoke solutions that bridge the gap between frontier AI products and practical application, addressing integration, data readiness, and state-management challenges.
- What is the application window for the Forward Deployed Engineer GenAI role?
- The application window will remain open until at least May 13, 2026. However, the posting notes that the opportunity may close sooner based on business needs.