This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Cloud Platform Engineer based in the United States.
The Staff Cloud Platform Engineer will shape and operate the cloud infrastructure powering advanced energy forecasting products, data pipelines, and AI-driven workloads. In this senior individual-contributor role, you will own critical components of a large-scale Azure and Kubernetes platform while setting technical direction across infrastructure, reliability, and security. You will lead complex infrastructure programs from initial design through deployment, ensuring production systems remain resilient, secure, and cost-efficient. Working closely with engineering, data science, and product teams, you will build scalable platform capabilities that accelerate development and improve operational performance. You will also strengthen observability, automate infrastructure management, and create secure environments for emerging AI agent workloads. This fully remote opportunity offers the chance to influence engineering standards within a globally distributed team working to modernize energy systems and support the energy transition.
Accountabilities:
You will lead the evolution of cloud infrastructure and platform engineering practices, balancing reliability, security, scalability, and cost efficiency across production environments. Your responsibilities will include:
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Kubernetes Platform Engineering: Operate and evolve multiple Azure Kubernetes Service (AKS) clusters supporting production services, workflows, and AI agent workloads. Manage technologies such as Karpenter, Cilium network policies, workload identity, External Secrets, Helm, and ArgoCD.
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Infrastructure as Code: Lead the development and maintenance of a large Terraform codebase, including provider upgrades, infrastructure drift reconciliation, reusable module design, and safeguards for reliable infrastructure changes.
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CI/CD and Automation: Maintain and improve GitHub Actions runners and build pipelines, supporting secure, efficient infrastructure deployment through tools such as Atlantis and GitOps-based workflows.
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Database Reliability: Operate and improve production data stores, including MySQL Flexible Server and self-managed ClickHouse. Strengthen replication, failover, backup and recovery, capacity planning, and upgrade procedures to maintain reliable data services.
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AI Platform Infrastructure: Design secure, isolated, and auditable environments for AI agent workloads and Model Context Protocol (MCP) services. Implement appropriate identity controls, network egress restrictions, observability, and self-service deployment capabilities for internal applications.
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Observability and Reliability: Develop the monitoring and observability stack using tools such as OpenTelemetry, Prometheus, Grafana, and Tempo. Maintain alerting rules as code, improve incident detection, and promote service-level objectives and dependable operational practices.
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Cloud Cost Optimization: Identify and implement opportunities to reduce Azure infrastructure spending while maintaining performance, reliability, and security.
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Incident Management and On-Call: Participate in a globally distributed on-call rotation, lead incident response, conduct blameless postmortems, and support engineering, data science, data engineering, and product teams.
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Technical Leadership: Lead multi-month infrastructure initiatives from design documentation and stakeholder alignment through phased rollout, cutover, and cleanup. Establish technical direction and drive improvements across platform engineering.
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Mentorship and Documentation: Review code, write design documents, mentor engineers, and document systems and operational procedures to promote knowledge sharing and reduce dependence on individual team members.
Requirements:
The ideal candidate is an experienced infrastructure or platform engineer with deep production expertise, strong technical judgment, and a track record of leading complex infrastructure initiatives. Required qualifications and skills include:
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Professional Experience: 8+ years in infrastructure engineering, platform engineering, site reliability engineering, or related fields, including several years of senior-level ownership of production systems.
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Program Leadership: Demonstrated ability to lead multi-month infrastructure projects end to end, including technical design, stakeholder alignment, phased implementation, cutover, and post-deployment cleanup.
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Kubernetes Expertise: Extensive hands-on experience operating Kubernetes in production, ideally using a managed service such as AKS, Amazon EKS, or Google Kubernetes Engine (GKE), with strong knowledge of networking and network policies.
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Cloud Infrastructure: Production experience with at least one major cloud provider. Azure expertise is strongly preferred; candidates with deep AWS or GCP experience should be willing to develop substantial Azure expertise.
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Infrastructure as Code and GitOps: Strong Terraform skills in large codebases and experience with GitOps-oriented workflows and tools such as Atlantis, ArgoCD, or equivalent solutions.
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Database Operations: Experience operating relational or analytical databases in production, such as MySQL, PostgreSQL, or ClickHouse, including replication, upgrades, recovery, and reliability management.
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Security Engineering: Practical understanding of least-privilege access, identity-based authentication, secrets management, and network isolation, with security integrated into everyday engineering practices.
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Observability and SRE Practices: Experience with metrics, logs, distributed tracing, alerting, and service-level objectives, ideally using OpenTelemetry and related observability tools.
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Automation and Scripting: Proficiency in Python and shell scripting for infrastructure automation, operational tooling, and workflow improvements.
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Communication and Collaboration: Strong written communication skills, with the ability to produce clear design documents, code reviews, and asynchronous updates while collaborating across distributed teams and time zones.
Additional experience that would be advantageous includes:
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Operating ClickHouse at scale, including clustering and replication.
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Managing Argo Workflows or other high-volume batch processing and workflow platforms.
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Working with Cilium, Karpenter, or node auto-provisioning solutions on AKS.
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Building infrastructure for AI agents or large language model workloads, including sandboxing, egress controls, model gateways, or Azure AI Foundry.
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Using AI coding agents, such as Claude Code, as part of daily engineering workflows.
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Supporting compliance initiatives such as SOC 2 or ISO 27001.
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Applying FinOps practices to optimize Azure cloud spending.
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Working with energy, utilities, or time-series data platforms.
Benefits:
The compensation and benefits package is designed to support flexibility, professional collaboration, and employee well-being across a distributed team. Benefits include:
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Competitive Compensation: Competitive salary based on geographical location, plus a stock option package.
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Healthcare Coverage: Medical, dental, and vision insurance.
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Flexible Paid Time Off: Flexible PTO policy to support personal needs and work-life balance.
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Remote Work: Fully remote working arrangements for candidates based in the UK, EU, or US time zones, with at least three hours of daily overlap with US Central Time required.
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Flexible Working: Work within your local hours, including on-call shifts scheduled to accommodate your time zone.
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Annual Company Retreat: An opportunity to connect in person with colleagues from across the global organization at least once a year.
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Collaborative Global Team: Work alongside specialists in energy, software engineering, AI, machine learning, and SaaS.
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Meaningful Mission: Contribute to technology designed to improve grid reliability, optimize energy assets, and accelerate decarbonization.