Platform Architect, InCommand

Team: InCommand

Location: Remote, USA

Commitment: Full-Time

Workplace Type: remote

Salary:

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 organisations, 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.