Forward Deployed Engineer, GCC (French, German)

Google; Greater London; On-site; GBP 160,000 - 200,000; Full time

Job summary

Google London seeks a senior AI engineer to lead the development of complex AI applications and transition rapid prototypes into production-grade agentic workflows that deliver measurable ROI.

You will design connective tissue between our AI products and customer live infrastructure, including APIs, data silos, and security perimeters, while building high-performance evaluation pipelines for accuracy, safety, and latency.

Qualifications

• Bachelors degree or equivalent practical experience.
• 2 years of software development experience or 1 year with an advanced degree.
• 1 year of ML infrastructure experience (model deployment/evaluation/data processing/debugging).
• Experience with GenAI techniques (LLMs, multimodal, or vision models).
• Ability to communicate fluently in French and German for client relationships in this region.
• Masters or PhD in AI, CS, or related field.
• Experience implementing multi-agent systems using LangGraph, CrewAI, or ADK with patterns like ReAct, self-reflection, hierarchical delegation.
• Knowledge of LLM metrics (tokens/sec, cost-per-request) and state management tracing.
• Ability to implement secure agentic workflows with MCP, tool-calling, and OAuth authentication.

Responsibilities

• Lead development of complex AI applications and production-grade agentic workflows.
• Design APIs and connect AI products to customer live infrastructure (APIs, data silos, security perimeters).
• Develop high-performance evaluation pipelines and observability frameworks for accuracy, safety, and latency.
• Identify repeatable patterns and friction points to create reusable modules or feature requests.
• Partner with customer engineering teams to ensure Google-grade development practices and long-term adoption.

Skills

GenAI techniques

Multi-agent systems

Secure workflows

MCP/OAuth

LLM metrics

Education

Bachelor's degree or equivalent

Master's or PhD in AI/CS

Tools

LangGraph

CrewAI

ADK

Job description

Salary: £160,000 - 200,000 per year

Requirements:

• Bachelors degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
• 1 year of experience with ML infrastructure, such as model deployment, model evaluation, data processing, or debugging.
• Experience with GenAI techniques, such as LLMs, multi-modal, or large vision models, or with GenAI-related concepts such as language modeling or computer vision.
• Ability to communicate fluently in French and German to support client relationship management in this region.
• Masters degree or PhD in AI, Computer Science, or a related technical field.
• Experience implementing multi-agent systems using frameworks such as LangGraph, CrewAI, or Googles Agent Development Kit (ADK), and complex patterns like ReAct, self-reflection, and hierarchical delegation.
• Knowledge of LLM-native metrics such as tokens/sec and cost-per-request, and techniques for optimizing state management and granular tracing.
• Ability to implement secure agentic workflows incorporating MCP, tool-calling, and OAuth-based authentication.

Responsibilities:

• Lead development of complex AI applications, transitioning rapid prototypes into production-grade agentic workflows that drive measurable return on investment.
• Design and code the connective tissue between our AI products and customer live infrastructure, including APIs, legacy data silos, and security perimeters.
• Develop high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency.
• Identify repeatable field patterns and technical friction points in our AI stack, and convert them into reusable modules or formal product feature requests for our engineering teams.
• Partner with customer engineering teams to instill Google-grade development best practices and support long-term project success and high end-user adoption.

Technologies:

• AI
• Cloud
• Computer Vision
• Support
• LLM
• MCP