Principal AI Architect (Google Cloud)

Overview

In this role you will shape enterprise-scale cloud architectures for key projects and guide clients through AI, data and migration initiatives. You’ll lead architecture discussions with customers and prospects, provide pre- and post-sales technical guidance, and help build next-generation ML products. You work closely with cross-functional teams to ensure scalable, production-grade solutions that align with Datatonic’s AI and data strategy. This is a customer-facing role that blends technical leadership with strategic influence, across Google Cloud and partner ecosystems.

Pay / Benefits

• Holiday: 25 days plus bank holidays
• Private health insurance and Smart Health Services
• Gym membership discounts
• WFH/hybrid and relocation allowances
• Udemy learning platform access
• Pension with employer contributions and progression to 10%

Responsibilities

• Evaluate and design enterprise-scale Data and AI architectures for client programs
• Lead architecture reviews and provide actionable recommendations to senior stakeholders
• Mentor and develop the architecture team, promoting technical excellence
• Collaborate with sales to scope solutions and support technical pre-sales engagements
• Partner with GTM teams to create market-ready solutions and governance frameworks
• Define and embed technical best practices across project delivery
• Contribute to internal knowledge base and thought leadership materials
• Collaborate with partners (Google Cloud, Tableau, Looker) to leverage technology effectively
• Provide technical leadership during customer engagements and ensure successful delivery

Key requirements

• Hands-on design and implementation experience of large-scale big data cloud architectures
• Proven ability to manage projects from conception to completion
• Strong analytical skills and focus on technical excellence
• Exceptional communication and stakeholder management skills
• Extensive pre-sales experience and ability to champion innovative proposals
• End-to-end production-grade cloud technology knowledge (data, security, networking)
• Experience with container technologies
• Proficiency in Python, Java and SQL
• Experience delivering scalable, robust, high-performing solutions
• Bachelor’s in Computer Science or related discipline

• Effective verbal and written communication
• Stakeholder management
• Mentorship and leadership
• Cloud architectures (Google Cloud, AWS)
• Data engineering and analytics tooling
• ETL and data pipelines (Spark, Beam, Flink)

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