Forward Deployed Engineer III, Cloud, Applied AI

Forward Deployed Engineer III, Google Cloud, Applied AI

_corporate_fare_ Google _place_ San Francisco, CA, USA;
Atlanta, GA, USA; +6 more; +5 more

** Mid*
* Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

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XApplicants in San Francisco:
Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.

Note:

By applying to this position you will have an opportunity to share your preferred working location from the following:
** San Francisco, CA, USA;
Atlanta, GA, USA;
Austin, TX, USA;
Addison, TX, USA;
Detroit, MI, USA;
Houston, TX, USA;
Sunnyvale, CA, USA** .

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* Minimum qualifications:

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* + 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., 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.

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* Preferred qualifications:

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* + Master's degree or PhD in AI, Computer Science, or a related technical field.

+ Experience implementing multi-agent systems using frameworks like ReAct and self-reflection.

+ 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 RAG chunking to prevent hallucinations.

+ Ability to travel up to 50% of the time.

+ Track record of troubleshooting live, high-traffic systems during critical windows.

** About the job*
* As a Forward Deployed Engineer (FDE) in Applied AI, you are the "Agent Engineer" and the primary driver for our customers' most critical AI initiatives. You take initial conversational prototypes and transform them into production-ready solutions, owning the end-to-end engineering lifecycle, including the transition from "Art of the Possible" to real-world business value and scalable, secure AI systems. 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.

This role requires an understanding of software engineering, machine learning operations, and cloud infrastructure.

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 '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 Deep Mind'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: $174000 - $253000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google () .

** Responsibilities*
* + Serve as the lead developer for conversational artificial intelligence (AI) and customer experience (CX) applications, transitioning from rapid prototypes to production-grade agentic workflows.

+ Architect and code conversational flows that are not just functional, but optimized for the "connective tissue" between Google's Conversational AI products and customers' live infrastructure, including APIs, legacy data silos, and security perimeters.

+ Build high-performance evaluation (Eval) pipelines and observability frameworks…