AI Sales Specialist, Startups and Scale Ups

On-site in London·Added 25 days ago

Google

168 open roles

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Overview

Requirements

Work on-site in London
No relocation package mentioned.
Have 10+ years of experience
Senior-level role.

Skills

Nice to have

Requirements

Minimum qualifications:

Bachelor's degree or equivalent practical experience.
10 years of experience in enterprise technology sales.
3 years of experience in Cloud, Data, Analytics, or AI/ML.
Experience with regulatory and operational data in start-up industries.

Preferred qualifications:

Experience selling Large Language Models (LLMs), agents, or generative technologies.
Experience working at a cloud provider, system integrator, or AI-native firm.
Ability to explain AI agents, RAG (Retrieval-Augmented Generation), fine-tuning, vector search, and inference scaling and why they matter to business audiences.
Ability to demonstrate success building business cases involving complex consumption economics.
Track record of territory planning, stakeholder mapping, and executing complex, multi-stage agreement cycles.

The role

The Google Cloud Platform team helps customers transform and build what's next for their business - all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers - developers, small and large businesses, educational institutions and government agencies - see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.

As an Artificial Intelligence (AI) Commercial Lead, you will direct enterprise modernization from experimental phases toward live deployment. You will sit at the intersection of engineering depth and business strategy, assisting accounts as they evolve initial proof-of-concepts into resilient, high-capacity frameworks that generate measurable financial returns.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.

Responsibilities

Guide customers through the pilot-to-production journey, distinguish between model Application Programming Interfaces (APIs) and full platform value, and drive scalable decisions.
Shift conversations to business cases, model platform Total Cost of Ownership (TCO), explain inference cost scaling, and articulate the Return on Investment (ROI) of build versus buy decisions.
Navigate value patterns such as business generation (e.g., customer experience), efficiency (e.g., automation), and decision augmentation (e.g., insight).
Position AI Agents within the context of the industry, and explain how data proximity, governance, and operational coherence (e.g., Machine Learning Operations [MLOps]) on Vertex AI create an engaged advantage.
Leverage a team of Field Sales Representatives and Customer Engineers, and activate Partners to scale industry-specific plays and accelerate implementation. Distinctively assess agreement maturity, and commit to defendable numbers based on technical reality and executive sponsorship.

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.