Job Description

Minimum qualifications

• Bachelor's degree or equivalent practical experience.
• 6 years of experience with cloud native architecture in a customer-facing or support role.
• Experience engaging with, or presenting to, technical stakeholders or executive leaders.
• Experience working directly within or as a technical advisor to venture-backed startups or scaleups.

Preferred qualifications

• Experience as a CTO, lead architect, or head of engineering at a startup, or equivalent experience navigating fast-paced startup lifecycles.
• Strong understanding of modern data warehouse architectures, real-time analytics, and data governance (e.g., BigQuery, Spark, Kafka).
• Deep technical expertise in Generative AI development (e.g., prompt engineering, model tuning, vector databases like Vertex AI Vector Search, and AI frameworks like LangChain or LlamaIndex).
• Active participation in the startup and AI ecosystem, with a track record of public speaking, technical writing, or community contribution.

Experience engaging with, or presenting to, technical stakeholders or executive leaders.

Experience engaging with, or presenting to, technical stakeholders or executive leaders.

Experience as a CTO, lead architect, or head of engineering at a startup, or equivalent experience navigating fast-paced startup lifecycles.

Experience as a CTO, lead architect, or head of engineering at a startup, or equivalent experience navigating fast-paced startup lifecycles.

Strong understanding of modern data warehouse architectures, real-time analytics, and data governance (e.g., BigQuery, Spark, Kafka).

Strong understanding of modern data warehouse architectures, real-time analytics, and data governance (e.g., BigQuery, Spark, Kafka).

Deep technical expertise in Generative AI development (e.g., prompt engineering, model tuning, vector databases like Vertex AI Vector Search, and AI frameworks like LangChain or LlamaIndex).

Deep technical expertise in Generative AI development (e.g., prompt engineering, model tuning, vector databases like Vertex AI Vector Search, and AI frameworks like LangChain or LlamaIndex).

Active participation in the startup and AI ecosystem, with a track record of public speaking, technical writing, or community contribution.

Active participation in the startup and AI ecosystem, with a track record of public speaking, technical writing, or community contribution.

Active participation in the startup and AI ecosystem, with a track record of public speaking, technical writing, or community contribution.

About the job

As a Customer Engineer in the UK/IE Startups & Scaleups Growth team, you will lead high-impact technical engagements with rapidly scaling, high-potential startups and VC-backed businesses. You will help startup founders, CTOs, and developers scale their products on Google Cloud. You will act as a trusted advisor, helping to accelerate their product delivery, optimize their technical architecture, and drive strategic business outcomes.

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

• Deliver compelling presentations, product demonstrations, and technical workshops at Google events, accelerator programs (e.g., Plug n Play, local startup hubs), and industry conferences.
• Build and nurture strong, trusted-advisor relationships with startup CTOs, founders, lead architects, and engineering teams.
• Help customers design and scale modern data platforms using BigQuery, real-time streaming, and vector databases as the core foundation for their application logic and AI capabilities.
• Guide startups on implementing advanced AI workloads, including Generative AI, Large Language Models (LLMs), RAG systems, and agentic workflows, utilizing both first-party (Gemini) and partner model ecosystems (e.g., Anthropic).
• Partner with the Sales team to qualify opportunities, address technical objections, and design secure, scalable, and cost-effective cloud architectures.

Build and nurture strong, trusted-advisor relationships with startup CTOs, founders, lead architects, and engineering teams.

Build and nurture strong, trusted-advisor relationships with startup CTOs, founders, lead architects, and engineering teams.

Help customers design and scale modern data platforms using BigQuery, real-time streaming, and vector databases as the core foundation for their application logic and AI capabilities.

Help customers design and scale modern data platforms using BigQuery, real-time streaming, and vector databases as the core foundation for their application logic and AI capabilities.

Guide startups on implementing advanced AI workloads, including Generative AI, Large Language Models (LLMs), RAG systems, and agentic workflows, utilizing both first-party (Gemini) and partner model ecosystems (e.g., Anthropic).

Guide startups on implementing advanced AI workloads, including Generative AI, Large Language Models (LLMs), RAG systems, and agentic workflows, utilizing both first-party (Gemini) and partner model ecosystems (e.g., Anthropic).

Partner with the Sales team to qualify opportunities, address technical objections, and design secure, scalable, and cost-effective cloud architectures.

Partner with the Sales team to qualify opportunities, address technical objections, and design secure, scalable, and cost-effective cloud architectures.

Partner with the Sales team to qualify opportunities, address technical objections, and design secure, scalable, and cost-effective cloud architectures.