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Forward Deployed Engineer, Applied AI

On-site in London·Added 17 days ago (last checked 1 Oct)

Google

168 open roles

Overview

Requirements

  • Work on-site in London

    No relocation package mentioned.

  • Have 5+ years of experience

    Mid-level role.

Skills

Nice to have

Requirements

What we're looking for

  • 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 using 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.

Nice to have

  • Master’s 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 Retrieval-augmented generation (RAG) chunking to prevent hallucinations.
  • Track record of troubleshooting live, high-traffic systems during critical windows.
  • Ability to travel up to 50% of the time.

Pay & benefits

What you'll get

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

France: €104000 - €106000 (EUR) + 15% bonus target + equity + benefits

The role

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 life-cycle, including the transition from "Art-of-the-Possible" to real-world business value and scalable, secure AI systems. In this high-travel, high-impact role, you will be focused on leading technical delivery for Conversational AI pilots and establishing the first Customer User Journeys (CUJs) for our largest customers at their sites. You will require a deep understanding of software engineering, machine learning operations, and cloud infrastructure.

What you'll do

  • Serve as the lead developer for complex Conversational AI and CX applications, transitioning from prototypes to production-grade agentic workflows (e.g., multi-agent systems, Model Context Protocol (MCP) servers) that drive measurable return on investment.
  • Architect and code conversational flows that are functional and 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 to optimize agentic workloads, focusing on reasoning loops, tool selection, and reducing latency while maintaining production-grade security and networking.
  • Identify repeatable field patterns and technical "friction points" in Google's AAI stack, converting them into reusable modules or product feature requests for 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.

Hiring process

4 steps3 interviewsa task to do6–8 weeks in all
  1. Apply online

  2. Assessments

    Online test · Not every role

    You may be asked to take the Google Hiring Assessment (workstyle skills) and, for some roles, role-related assessments such as a coding exercise.

  3. Recruiter conversations

    With a recruiter · Phone call · 1–2 sessions

    One or two shorter conversations assessing key skills, sharing information about the organisation and team, and asking about your preferences such as location.

  4. Project work

    In your own time · Not every role

    For some roles, a small project before interviews: a case study, writing or code samples.

  5. Interviews

    With a rotating cast of Googlers

    A panel of structured interviews, over video or in person, with a rotating cast of Googlers; open-ended role-related questions scored against the same rubric for every candidate, no brainteasers.

  6. Decision and offer · With a recruiter

  • Structured interviews: every candidate for a role is scored against the same rubric; no brainteasers.
  • AI tools are not permitted during interviews.
  • For some roles, pre-selected interviews happen virtually before final interviews onsite.

About Google

Industry
Technology
Founded
1998
Employees
100,000+
Headquarters
Mountain View, USA
Website
google.com

In their own words

About the company & team

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.

Additional information

Learn more about benefits at Google. Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Paris, France; Zürich, Switzerland; London, UK.

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