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About Gyre Energy
Gyre Energy cuts costs for cooling-intensive operators by transforming how cooling systems use energy. Cooling represents 20% of global electricity demand, driving up to 40% of electricity costs for data centres and 90% for cold storage facilities. Gyre’s platform uses advanced AI and low-cost thermal storage to reduce energy use and unlock large-scale distributed flexibility for cooling assets. Our mission is to create a smarter, cleaner energy future by turning cooling loads into a flexible, grid-supportive asset.
Backed by one of Europe’s leading VCs and working with major industry partners, Gyre Energy is building the foundational infrastructure to help large-scale cooling operators lower costs, reduce emissions, and support the energy transition.
About the Role
We’re hiring a Senior Backend Engineer to own the infrastructure layer of a novel AI platform that sits at the intersection of physics-based modelling, real-time IoT data, and autonomous control of physical cooling systems at scale.
You’re joining at a moment of real growth: we’re scaling from our first set of enterprise sites to be able to address 50, 100, and 1000+, deploying AI models to industrial edge devices, and building the infrastructure that will underpin a platform controlling significant cooling loads around the world (currently deployed in the UK, West Africa, and the Americas). You’ll be tackling interesting engineering challenges: real-time sensor data at scale, ML model deployment to constrained hardware, fleet management across geographically distributed sites, and the security posture required to operate inside enterprise critical infrastructure.
You’ll work directly with our CTO and fellow Engineers, taking ownership of cloud infrastructure, IoT fleet management, DevOps, and security, shaping how we build as we scale.
Key Responsibilities
Short-Term Objectives (first 100 days):
- Take ownership of our Azure cloud infrastructure and further build best practices across compute, networking, storage, and security
- Harden our enterprise security posture across our stack
- Further our CI/CD pipeline: automated testing, deployment, and rollback for both cloud backend and edge device code
- Expand our fleet management via Azure IoT Hub, enabling device configuration, provisioning, and over-the-air updates at scale
- Work closely with AI engineers to build the infrastructure needed to deploy and serve ML models at the edge
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Long-Term Objectives:
- Scale our backend architecture to support 50, 100, and 1000+ enterprise sites without fundamental rework
- Establish robust dev/staging environments and cloud-provider portability: Azure-first, with the flexibility to move
- Own our MLOps infrastructure: model registry, automated validation pipelines, drift monitoring, and per-site model management as the fleet grows
- Support our ISO 27001 certification programme, building the controls, audit trails, and access management that enterprise clients expect
- Deploy and integrate our physics simulator into production cloud infrastructure
- Contribute to or lead development of a customer-facing dashboard
- Help define engineering culture, tooling, and practices as a founding member of the infrastructure function
What We’re Looking For
Required:
- Hands-on Azure experience: AKS, App Services, Key Vault, VNet/NSG, RBAC, Azure IoT Hub
- Terraform and/or Bicep: designing and managing multi-environment cloud infrastructure from scratch
- Docker and Kubernetes: containerised workloads in production
- Azure IoT Hub and Device Provisioning Service (DPS): fleet management, device twins, zero-touch provisioning
- PostgreSQL / TimescaleDB at scale: time-series query optimisation, continuous aggregates
- MQTT and other IoT data ingestion patterns
- Python backend development and API design (REST)
- CI/CD pipeline ownership and build-from-scratch capability (GitHub Actions or Azure DevOps)
- AzureML Studio: model registry, deployment pipelines, experiment tracking
- ML inference pipeline deployment, including to constrained edge devices
- Production monitoring, observability, and alerting (Prometheus, Grafana, Azure Monitor)
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Preferred:
- Multi-cloud familiarity (AWS and/or GCP) for portability architecture
- Azure IoT Edge runtime: container-based edge deployment and OTA updates
- IoT Hub layered deployments and canary/ring-based rollout strategies
- Model drift monitoring and automated retraining triggers
- ISO 27001 or equivalent compliance experience (SOC 2, IEC 62443)
- React / Node.js full-stack development
- Industrial IoT, energy, or operational technology domain knowledge
- Ansible or equivalent for edge device bootstrapping automation
- Comfortable using AI tools to accelerate work (e.g. Claude Code, Codex, or other open source generative AI tools)
Why Join Us?
- Work on genuinely hard problems: physics-based AI, real-time control of physical systems, and ML deployment to constrained hardware are not solved problems. You’ll be building infrastructure that doesn’t have a standard playbook.
- Own it from day one: you’ll be the backend lead at a pre-Series A company. The decisions you make in the next 12 months will define our architecture for years.
- Your work has a physical footprint: the systems you build will directly control cooling assets, cut energy bills, and reduce carbon emissions at real industrial sites.
- Work at the frontier of applied AI: alongside engineers with deep Bayesian and reinforcement learning backgrounds, deploying models that interact with the physical world in real time.
- Backed by one of Europe’s leading VCs and growing fast: join before Series A, with meaningful equity and the career trajectory that comes with being an early engineer at a company with real traction.
- A small, senior team that moves fast and takes the work seriously and enjoys the challenge, with genuine autonomy over how things get built.
How to Apply
Send your CV and a short cover note to careers@gyreenergy.com
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