AI Innovation Engineer, Google Cloud

On-site in London·Added yesterday (last checked 15 Oct)

Google

249 open roles

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Overview

Skills

Nice to have

BigQuery

Requirements

Minimum qualifications:

Bachelor's degree in Computer Science, a related field, or equivalent practical experience.
8 years of experience in software or data engineering, including one or more programming languages (e.g., Python, Go, Java), and with design patterns, testing frameworks, and API contract design.
Experience using machine learning methodologies (deep learning, reinforced learning), model identification, selection and AI operations (e.g., model monitoring).
Experience using Generative AI and agentic orchestration utilizing frameworks (e.g., LangChain, CrewAI, or Vertex AI Agent Builder) and vector databases.

Preferred qualifications:

Experience in financial services, and with the regulatory and operational clearing, settlement, or custody.
Experience with FSI regulatory practices and data residency, encryption at rest/transit (CMEK), and "explainable AI" requirements in banking.
Experience with data modeling of relational, NoSQL, and analytical data modeling (Star Schema, Data Vault).
Experience in BigQuery, Vertex AI, Dataflow, and Pub/Sub with an ability to drive the discovery phase, moving from a vague business problem to a structured product requirement document (PRD) and a working technical demo.
Experience working in a high-maturity DevOps culture (e.g., trunk-based development, automated testing, blue/green deployments).

The role

In this role, you will accelerate customer value and increase adoption by delivering innovative, repeatable, and enterprise-ready solutions focused on business value. Make Google Cloud the preferred choice for customers by delivering the highest-value, industry relevant solutions.

Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

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

Germany: €150000 - €153000 (EUR) + 20% bonus target + equity + benefits

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: Frankfurt am Main, Germany; Zürich, Switzerland; Munich, Germany; London, UK.

Responsibilities

Design and build autonomous agentic workflows utilizing Machine Learning and generative AI technologies as part of a fully autonomous or human-in-the-loop agentic workflow.
Partner with client leads (business user) to identify high-impact AI use cases. Translate these into product requirement documents (PRDs), clearly defining critical user journeys (CUJs) and success metrics.
Evaluate and integrate AI solutions with modern data foundations, including relational databases, data lake houses, and real-time streaming architectures.
Ensure all prototypes are built with a "production-first" mindset. Implement basic CI/CD pipelines and utilize infrastructure-as-code (IaC) (e.g., Terraform) to ensure environments are reproducible and secure.
Create clear technical guides to ensure a seamless hand-off from proof-of-concept (POC) to engineering teams.

Hiring process

4 steps3 interviewsa task to do6–8 weeks in all

Apply online
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.
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.
Project work
In your own time · Not every role
For some roles, a small project before interviews: a case study, writing or code samples.
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.
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.