Customer Engineer, UK/IE Startups

About the job

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.

Qualifications

Minimum qualifications:

• Bachelor's degree in Computer Science, Engineering, a related technical field, or equivalent practical experience.

• 10 years of experience in a customer-facing technical role (e.g., Customer Engineer, Solutions Architect, or Developer Advocate) within the cloud computing industry.
• Experience designing, architecting, and deploying cloud-native applications, containerized environments (Kubernetes/GKE), and modern data pipelines.

Preferred qualifications:

• Experience working directly within or as a technical advisor to high-growth, venture-backed startups or scaleups.
• Background 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.