Platform Architect

Serverfarm is a leading developer and operator of data centers with over 750+ locations and key customer relationships in 45 countries. We're revolutionizing how data centers operate across North America, Western Europe, and Israel, serving the world's leading technology and hyperscale companies. With Manulife Investment Management's acquisition in 2023 and our award-winning InCommand platform, we're positioned for explosive growth as AI adoption and cloud migration drive unprecedented demand for data center capacity.

A career at Serverfarm means being at the forefront of digital infrastructure innovation, where your work directly impacts how the world's data is managed and secured. As we target 4x growth over the next four years, you'll have unprecedented opportunities to take on new challenges, develop cutting-edge skills, and grow your career across our expanding global operations.

Join our team of innovators and help shape the future of sustainable data centers while building a career without boundaries.

Key Accountabilities

• Build the foundation of the new platform yourself: the control plane and tenancy that everything else sits on, written with coding agents and the engineers who join you, and own the first code merged on the new platform.
• Design and own the unified data model and its evolution, publish it with the public API as a specification others build against, and define the platform architecture around it (data stores, identity and multi-tenancy, API layer).
• Own retrieval and query performance at telemetry scale: storage choices, query patterns for live consoles and for analytical and AI workloads, latency targets, tenant isolation at the data layer.
• Choose the technology stack and platform standards, and recommend the cloud the platform starts on and how it stays portable.
• Design how the platform integrates large language models and other AI services to deliver operational intelligence: insights, recommendations, and natural-language access to operational data.
• Define, in partnership with Integrations, the contract by which site data enters the platform.
• Give technical direction to the engineers who join the new platform in its first months, and set the patterns the team builds on.

Required Skills

• 10+ years building back-end and platform systems, and in the last three years you have personally shipped a multi-tenant SaaS platform or control plane on Kubernetes, writing production code, as the technical decision-maker.
• You have designed the domain data model for a complex operational system (assets, hierarchies, time series, events) and owned its evolution across releases, with the compatibility, versioning, and migration decisions that came with it.
• You have delivered retrieval performance at telemetry scale: chosen time-series and relational storage (PostgreSQL with TimescaleDB or equivalent, with a columnar engine such as ClickHouse for analytical and AI workloads), designed queries for live and analytical workloads over long histories, and met API latency targets.
• You have built hands-on on a major public cloud (GCP, AWS, or Azure) with Kubernetes and Helm, with judgment about when a managed service is the right call and when portability matters more.
• You have built identity, tenancy, and security by design into enterprise SaaS.
• You have designed and published an API or data-model specification that other teams, and ideally external organizations, built against, and written architecture decisions that engineers worked from.
• You have been a senior individual contributor on a platform's foundational production code.

Preferred Skills

• Used agentic coding tools and directed and reviewed agent-written code at volume.
• Knowledge of or experience with DCIM products: the data they manage and how data-center operators use them.
• Designed platform ingress with Kafka-compatible streaming (Kafka, Redpanda or equivalent) and MQTT brokers (EMQX, HiveMQ or equivalent).
• Instrumented a platform with OpenTelemetry for its own observability.
• Integrated large language models into a platform: a model gateway, retrieval over operational data, tool interfaces an assistant can call.
• Run a platform across public clouds, or shipped software both as a cloud service and in customer-hosted or air-gapped environments.