Head of Technology Agentic Platform, AMER

Your mission

As Head of Technology Agentic Platfom, you will own the design and delivery of enterprise-scale Google Cloud platforms for our clients. At Datatonic, "platform" means the full stack that use cases run on: cloud landing zones, enterprise data platforms, MLOps platforms and integrated Data & AI platforms. You'll lead the practice and stay close to the build.

Your core belief is that every platform we build should improve on the last, and every use case should be faster, safer and cheaper to deliver than the one before. You'll spot the patterns that recur across client engagements and turn them into internal assets (reusable templates and best practices) that let teams go from idea to production in weeks, not months. You'll pair this with an appreciation for strong enablement that allows client and Datatonic teams to rapidly become self-sufficient on the platforms we build.

You'll design platforms built for scale: capable of deploying and operating many data products and AI agents, serving many kinds of consumers: people using BI and reporting tools, applications calling APIs, and AI agents consuming data through MCP and other interfaces. You'll use agents to run platforms more efficiently, and you'll make the value of the platform visible by combining FinOps with capabilities that measure the business impact of every use case deployed on it.

What You’ll Do

• Platform strategy & architecture: Own the reference architectures for Google Cloud landing zones, data platforms (e.g. BigQuery, Knowledge Catalog, Looker), MLOps (Gemini Enterprise Agent Platform) and Data & AI platforms, ensuring they are secure, governed, scalable and aligned to client business goals.
• Templates & accelerators: Build and evolve a library of reusable platform templates (infrastructure-as-code modules, CI/CD pipelines, data product and agent blueprints) and drive their adoption so every new use case starts from a proven, production-ready baseline.
• Best practices & enablement: Define the standards, patterns and guardrails for how use cases are built on the platform, and lead enablement (playbooks, training, developer experience) so client teams can build confidently and independently.
• Scaling use cases: Put in place the capabilities needed to deploy data products and AI agents at scale: automated deployment, environment management, data contracts, evaluation and testing, observability, security, and governance across the use case lifecycle.
• Multi-consumption layers: Design consumption layers that serve both people and machines: semantic layers and BI/reporting tools, APIs, and MCP servers that expose governed data and tools to AI agents.
• Agentic platform operations: Design, build and deploy agents that help run the platform (e.g. incident triage, cost anomaly detection, access requests, policy and configuration drift, and routine operational tasks), improving reliability while reducing operational overhead.
• FinOps & value measurement: Embed FinOps practices (cost allocation, forecasting, unit economics, optimisation) and build the telemetry and reporting that connect platform cost to the business value delivered by each use case, so clients can see and prove ROI.
• End-to-end ownership: you will be the ultimate business owner for platforms in AMER. You will lead client conversations, scope builds, presentations, etc. being responsible for delivering strong business outcomes and platform-related revenue

Technical Expertise

• Google Cloud & Platform Foundations: Deep, hands-on expertise designing and delivering Google Cloud landing zones, enterprise data platforms, MLOps and Data & AI platforms in production.
• Platform-as-a-product thinking: A track record of building reusable templates, blueprints and golden paths, and evidence that they measurably accelerated use case delivery.
• Scaling data products & AI agents: Experience taking multiple data products and/or AI agents from prototype to production at scale, including deployment automation, evaluation, monitoring and governance.
• Modern consumption architectures: Understanding of semantic layers, BI tooling, APIs and agent-facing interfaces such as the Model Context Protocol (MCP), and how to design data platforms where agents, not just people, are first-class consumers.
• Agents for operations: Practical experience, or a strong point of view, on building or deploying agents (e.g. with Vertex AI / Agent Development Kit) to automate and optimise platform operations.
• FinOps & value: Experience implementing FinOps frameworks and observability/telemetry that tie cloud spend to business outcomes and use case ROI.
• Enterprise fundamentals: Strong grounding in cloud security, identity, networking, infrastructure-as-code (e.g. Terraform), CI/CD and production operations.

Read the job posting on the Datatonic site

Source: the Datatonic Ashby job board. We last checked this job 41 min ago. We first saw it 8 days ago. A job on a job board does not always mean that the team interviews people now. We found this job board in a public list. We did not yet compare it with the careers page of the company.