As a Gemini Enterprise Customer Experience (GECX) Forward Deployed Engineer (FDE) in Applied AI, you are the agent engineer and the primary driver for our customers most critical AI initiatives. You will take initial conversational prototypes and transform them into production-ready solutions, owning the end-to-end engineering life-cycle, including the transition from art of the possible to real-world business value and scalable, secure AI systems. You will have an understanding of software engineering, machine learning operations, and cloud infrastructure. This is a high-travel, high-impact role focused on leading technical delivery for conversational AI pilots and establishing the first Customer User Journeys (CUJs) for our largest customers at their sites.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.
Minimum qualifications:
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 5 years of experience with software development using Python or similar coding languages.
- Experience architecting AI systems on cloud platforms (e.g., Google Cloud Platform (GCP)).
- Experience deploying resources via Terraform or similar tools to automate the setup of agents, functions, or networking.
- Experience building full-stack applications that interact with enterprise IT infrastructures and developing external customer projects.
Preferred qualifications:
- Master’s degree or PhD in AI, Computer Science, or a related technical field.
- Experience debugging agent logic and optimizing tool selection, including tracing conversation IDs across microservices to identify and resolve failures in real-time.
- Experience connecting agents to enterprise knowledge bases and optimizing retrieval-augmented generation (RAG) chunking to prevent hallucinations.
- Experience in troubleshooting live, high-traffic systems during critical windows.