Jobs at Carbon3.ai

Supports the Chief People Officer and US-based Chief Technology Officer by managing executive diaries, inboxes, meetings, travel, correspondence, expenses, documents, and confidential information. Coordinates across UK and US time zones, prepares polished presentations and reports, maintains records in Microsoft 365 and SharePoint, and provides broader administrative and team coordination support. The role requires exceptional organisation, initiative, discretion, communication, and adaptability in a fast-paced startup environment.

Deliver technology and infrastructure projects across multiple teams and workstreams. Translate technical designs into delivery plans, manage dependencies, risks, actions, suppliers, and contractors, coordinate staged rollouts, resolve blockers, and support PMO reporting. Serve as the liaison between engineers, operations, suppliers, and leadership while improving project processes and documentation.

Leads Era4’s information security function across AI and HPC infrastructure, cloud, networks, compute, storage, OT environments, customer services, and corporate IT. Owns security architecture, risk, governance, monitoring, incident response, certifications, third-party assurance, customer security engagements, and regulatory readiness. The role builds and scales the security organization, establishes zero-trust and tenant-isolation standards, oversees MDR and incident management, and provides executive-level guidance to customers, partners, regulators, and company leadership.

Own end-to-end recruitment for specialist and technical roles across data centres and mission-critical infrastructure. Partner with hiring managers and leaders to define requirements, create sourcing strategies, headhunt passive candidates, build talent pipelines, assess technical experience, manage requisitions, and deliver a strong candidate experience through offer and onboarding handover.

Build AI-driven SRE tooling and agentic automation to triage, diagnose, and remediate infrastructure issues. Integrate LLM-powered agents with observability, ITSM, and infrastructure APIs, develop self-service tooling and ChatOps, tune event/alert intelligence, and convert runbooks into auditable executable automations while contributing to operational standards and incident learning.

Serve as the technical bridge between customers and internal teams to design, validate, and onboard AI infrastructure solutions across bare metal, BMaaS, Kubernetes and cloud-native platforms. Lead technical discovery, POCs, benchmarks, architecture reviews, reusable reference architectures, and customer workshops while influencing product roadmap and production readiness.

Own and improve day-to-day procurement operations, including supplier onboarding, due diligence, approvals, renewals, contract records, governance, reporting, and process automation. Partner with Legal, Finance, and internal teams to manage supplier performance, maintain accurate records, mitigate third-party risks, and scale procurement processes. The role also involves implementing supplier management tools, supporting audit readiness, and developing team members.

Own and improve supplier onboarding, supplier records, documentation, contract renewal tracking, and audit readiness. Maintain corporate and production asset registers from purchase through disposal, coordinating with IT, Tech, Finance, and internal stakeholders. Support GRC activities by providing evidence for SOC 2 and ISO 27001 third-party controls. The role requires strong procurement and supplier management experience, process ownership, contract interpretation, attention to detail, and comfort building workflows in a fast-growing startup.

Designs, implements, and operates Era4’s enterprise observability platform across AI infrastructure. Responsibilities include managing telemetry collection, Grafana-based monitoring, Kubernetes integrations, alerting, dashboards, distributed tracing, multi-tenant controls, object-storage-backed retention, and OpenTelemetry integrations. The role also develops Infrastructure-as-Code and GitOps automation, supports incident detection and root-cause analysis, validates resilience and disaster recovery, and establishes observability standards, SLIs, SLOs, security controls, and operational governance.

Serves as the dedicated technical partner for customers using Era4’s AI and HPC infrastructure. Responsibilities include onboarding, workload and capacity planning, cluster and network readiness, technical documentation, SLA and KPI reporting, incident escalation, root cause analysis, governance, and roadmap input. The role requires customer-facing technical experience, Linux troubleshooting, GPU infrastructure knowledge, data-centre networking, and familiarity with ITIL-aligned service processes.

Design, implement, and improve security controls across Kubernetes, cloud-native, and datacentre infrastructure. Secure networks and firewalls, integrate DevSecOps controls into CI/CD, lead vulnerability management, build detection/response capabilities, automate security workflows, and support incident response and threat hunting for GPU-accelerated and AI/ML platforms.

Designs and implements cloud, bare-metal, and Kubernetes-based AI infrastructure across networking, compute, GPU, and storage. Develops scalable automation and production services, models database schemas, creates technical documentation, defines integration tests, and delivers infrastructure components into production. Requires strong experience with cloud-native architecture, Infrastructure as Code, GitOps, software development, and version control.

Design and govern the end-to-end architecture of Era4’s Kubernetes-based AI infrastructure. The role develops platform blueprints, technical standards, high- and low-level designs, multi-tenant GPU cloud architectures, capacity plans, and technology roadmaps. It coordinates Kubernetes, GPU, networking, storage, automation, security, observability, billing, and cloud services while guiding platform engineering and operations teams toward secure, scalable, reliable, and commercially viable solutions.

Design, deploy, operate, and continuously improve Kubernetes-based AI infrastructure. Responsibilities include managing Linux systems, bare-metal servers, data-centre infrastructure, NVIDIA GPU workloads, infrastructure automation, security access, platform governance, troubleshooting, documentation, customer and vendor collaboration, and on-call operational support.

Design, deploy, and operate large-scale GPU-accelerated HPC and AI clusters. Manage scheduling (Slurm), networking (InfiniBand/Ethernet), provisioning, automation, monitoring, incident response, security/RBAC, and vendor engagement to ensure high availability and performance for AI workloads.