Role Summary:
We are looking for a DevOps Engineer to design, operate and continuously improve our Kubernetes-based AI infrastructure. This hands-on role will focus on cloud-native platform engineering, GPU-accelerated workloads, bare-metal servers, automation and systems reliability, helping to deliver a secure, scalable and high-performing AI platform for ML engineers, data scientists and enterprise customers.

You will help build and operate our AI infrastructure, supporting Linux systems, Kubernetes platforms and automation initiatives. Working alongside experienced engineers and technology partners, you’ll contribute to the delivery of secure, reliable and scalable services.

Responsibilities:

• Deploy and maintain bare-metal servers, Linux systems and data-centre infrastructure.
• Configure, support and troubleshoot Kubernetes clusters and workloads.
• Manage NVIDIA GPU infrastructure, monitoring performance and resource utilisation.
• Automate infrastructure and operational processes using IaC and DevOps tools.
• Support security, access management and platform governance.
• Collaborate with engineering teams, vendors and customers to resolve technical issues.
• Produce technical documentation and support infrastructure deployments.
• Participate in operational support and on-call activities.

Required Skills & Experience:

• Experience working with Linux servers and infrastructure environments.
• Exposure to bare-metal hardware, data centres or enterprise platforms.
• Knowledge of Kubernetes and containerised environments.
• Understanding of NVIDIA GPUs, AI infrastructure or high-performance computing environments.
• Familiarity with Infrastructure-as-Code, automation and scripting tools.
• Experience with technologies such as Ansible, Git, YAML, Python or CI/CD pipelines.
• Strong troubleshooting skills and willingness to learn new technologies.
• Ability to work across infrastructure, platform and operational environments.

Why Join Era4:

You’ll be joining a mission-driven start-up building critical national infrastructure, where operational excellence directly enables growth. This role offers high visibility with leadership, real autonomy, and the chance to shape how a next-generation company operates at scale.

Diversity & Inclusion:

Era4 is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Note:

We appreciate this is a relatively new skill set and we are open to candidates who may not tick all the boxes but are willing to learn and develop their skillset.

We are seeking a Platform Developer to contribute to the technical architecture, design, and implementation of our cloud infrastructure and applications. In this role you will work to devise and realise technical components, including software, of new production environments and to deliver technical change into existing environments.

The successful candidate will employ their professional experience of automation, schema modelling, and software development with their knowledge of cloud infrastructure in our collaborative culture.

Key Responsibilities:

Technical Components:

• Contribute to the technical architecture and design of significant aspects of our bare metal and Kubernetes-based AI infrastructure, across networking, compute, GPU, storage.
• Production of high-level and low-level design documentation.
• Specification of acceptance and integration tests.
• Work with Project Managers, other developers, and operational teams to successfully deliver technical components into production environments.

Software Development:

• Prototyping, definition, and realisation of scalable and maintainable software solutions for automation and services.
• Active participation in software development processes.

Essential Experience:

• Significant contribution to technical architecture/engineering of infrastructure, cloud, platform.
• Designing Kubernetes and cloud-native solutions for operation at scale.
• Delivery of technical documentation to a high standard.
• Database schema modelling (relational database and/or graph database).
• Strong understanding of automation, Infrastructure-as-code, GitOps (preferably including Ansible).
• Software development for production services (preferably including Python, Go).
• Version control using git.

One or more would be an advantage:

• Experience of building significant cloud services.
• Experience of working with industry partners.
• Contribution to relevant open-source projects.
• Understanding/awareness of AI/ML system design.

Why Join Era4:

You’ll be joining a mission-driven start-up building critical national infrastructure, where operational excellence directly enables growth. This role offers high visibility with leadership, real autonomy, and the chance to shape how a next-generation company operates at scale.

Diversity & Inclusion: 

Era4 is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Role Summary: 

We are looking for Platform Engineer (HPC & AI) who can assist in shaping our new Platform team, this role will be customer facing, involve technical troubleshooting, and collaboration with vendor engineering teams to ensure seamless AI platform operations.

Responsibilities: 

• Designing, deploying, and managing large‑scale HPC and GPU‑accelerated clusters, including NVIDIA based compute environments.

• Implementing and administering HPC scheduling and resource‑management systems (e.g., Slurm), including GPU partitioning, workload scheduling, and capacity planning.

• Architecting and optimising InfiniBand and Ethernet network topologies.

• Ensuring high availability and resilience through failover strategies, planned maintenance coordination, and proactive risk mitigation.

• Automating provisioning, configuration, monitoring, and operational workflows across multi‑vendor HPC hardware and software stacks.

• Monitoring real‑time performance and leading troubleshooting efforts across compute, storage, interconnect, drivers, and node failures, engaging vendor support for critical issues.

• Incident response: node failure management, network issues, driver issues, troubleshooting common issues and then working with vendor support to resolve any critical issues.
• Security and access control: Manage user permissions, RBAC, security hardening, data protection.

Required Skills & Experience: 

• Experience supporting HPE PCAI or other AI/HPC infrastructure and platforms.

• System administration experience with OS’s like RHEL/CentOS, Ubuntu, tuning Linux kernel.

• Proficiency with Ansible, Nvidia and CUDA toolkits, Kubernetes and container orchestration.

• Understanding of automation, monitoring and security with GPU as a service.

• Extensive experience in system engineering, platform operations or SRE.

• Experience with GPU resource allocation (across instances, GPUs count and time).

• Advanced networking skills with High performance networking, troubleshooting and fine tuning.

• Familiarity with cloud-based platforms, APIs, and distributed systems.

• Understanding of AI/ML concepts and tooling (model training, inference, data pipelines basics).

• Experience with monitoring/logging tools (e.g., Grafana, Kibana, Splunk).

• Excellent communication skills to interface with both customers and internal / vendor teams.

• Good understanding of tools requirements for ML engineers and data scientists, and how to optimise the experience.

Why Join Era4:

You’ll be joining a mission-driven start-up building critical national infrastructure, where operational excellence directly enables growth. This role offers high visibility with leadership, real autonomy, and the chance to shape how a next-generation company operates at scale.

Diversity & Inclusion:

Era4 is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Note:

We appreciate this is a relatively new skill set and we are open to candidates who may not tick all the boxes but are willing to learn and develop their skillset.

We are seeking a Security Engineer to design, implement, and continuously improve security controls across our next-generation AI infrastructure and datacentre operations. This role focuses on protecting Kubernetes-based and cloud-native environments, securing our datacentre networking and infrastructure stack, strengthening security posture, identifying and mitigating risks, and enabling secure software delivery practices.

You will work closely with engineering, platform, and operations teams to integrate security into Era4’s proprietary cloud infrastructure, datacentre networks, CI/CD pipelines, containerized workloads, GPU-accelerated compute, and AI/ML platforms. The successful candidate will combine hands-on technical expertise with a proactive approach to threat detection, vulnerability management, and security automation across our brownfield-to-modern bare metal and cloud infrastructure environments.

Key Responsibilities:

Cloud & Infrastructure Security

• Design, implement, and maintain security standard and controls for on prem Kubernetes.
• Review infrastructure architectures and perform security assessments to identify risks and recommend mitigations.

Application & DevSecOps Security

• Integrate security controls into CI/CD pipelines, including SAST, DAST, dependency scanning, container image scanning, and secrets detection.
• Partner with development teams to implement secure coding practices and remediate security findings.
• Conduct threat modelling and security reviews for new applications, services, and infrastructure changes.

Vulnerability & Risk Management

• Lead vulnerability identification, prioritisation, remediation, and reporting activities across infrastructure and applications.

Detection & Response

• Develop and maintain security monitoring, alerting, detection capabilities and incident response playbooks.
• Investigate security incidents, perform root cause analysis, and coordinate remediation activities.

Security Automation

• Build automation to improve security monitoring, compliance validation, vulnerability management, and incident response workflows.
• Leverage Infrastructure as Code and policy-as-code frameworks to enforce security standards at scale.

Required Qualifications & Experience

• Experience in Security Engineering, Cloud Security, DevSecOps, Infrastructure Security, or Datacentre Security.
• Hands-on experience with vulnerability management platforms and security assessment methodologies.
• Familiarity with CI/CD security controls, secure software development practices, and supply chain security.
• In-depth scripting and automation skills using Python, Bash, or similar languages.

Nice to have:

• Experience securing AI/ML or GPU-based infrastructure, datacentre network security, firewalls, and network segmentation (Palo Alto firewalls, OpnSense, Nokia networking, or similar).
• Familiarity with compliance frameworks such as SOC 2, ISO 27001, NIST CSF, CIS Benchmarks, or PCI DSS.
• Experience with threat modelling, penetration testing, or red team engagements.
• Security certifications such as CISSP, GSEC, GCIH, GCIA, CCSK, CCSP, or relevant cloud security certifications.

Why Join Era4:

You’ll be joining a mission-driven start-up building critical national infrastructure, where operational excellence directly enables growth. This role offers high visibility with leadership, real autonomy, and the chance to shape how a next-generation company operates at scale.

Diversity & Inclusion:

Era4 is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Role Summary:

We are seeking an AI Infrastructure Validation Engineer to join our fast-scaling team. This role sits within Product but works across Product, Engineering and Operations. You will design, build, and orchestrate the automated preflight validation suites and performance benchmarks that continuously verify our bare-metal APIs, Kubernetes environments, and multi-node GPU clusters under enterprise-scale workloads.

You will ensure that every platform release, infrastructure change or hardware deployment is tested, validated and production-ready before reaching customers. This is an opportunity to join a mission-led AI business that is redefining infrastructure, intelligence, and impact for enterprise customers.

Key Responsibilities:

Software-Defined Infrastructure Validation & Preflight Automation:

• Design and build zero-dependency, Python-based “preflight” verification tools to validate multi-node distributed initialization, master-to-worker rendezvous routing, and correct GPU-to-CPU process affinity prior to launching massive model-training workloads.
• Write and maintain Infrastructure as Code to provision, configure, test, and teardown complex bare-metal and containerized compute environments.
• Implement Resilient Execution: Construct adaptive, intelligent test orchestration harnesses that can autonomously detect environment drifts and analyse platform changes.

GPU Platform & Low-Latency Network Validation:

• Automate the execution and results aggregation of cluster-level benchmarking suites and high-performance storage benchmarks to validate node-to-node throughput limits.
• Build validation routines to monitor high-throughput network fabrics, evaluating traffic patterns, congestion control parameters.
• Script low-level automated checks to validate server-node topology, PCIe link speeds, HBM memory status, secure boot parameters, and firmware performance via BMC, IPMI, or Redfish interfaces.

Continuous Integration & Observability:

• Integrate automated infrastructure validation suites directly into CI/CD pipelines.
• Configure and maintain observability pipelines to route real-time diagnostic logs and hardware execution metrics to quickly isolate slow, misconfigured, or degrading compute nodes.
• Partner with the Platform team, Network Engineers, and Datacentre Operations to lead root-cause analysis on complex platform regressions, hardware-software boundaries, and distributed interconnect bottlenecks.

Essential Experience:

• Strong proficiency in Python for building zero-dependency verification tools, automated test orchestration harnesses, and low-level system checks.
• Deep hands-on experience writing and maintaining Infrastructure as Code to provision, configure, and teardown complex bare-metal and containerized compute environments.
• Proven experience working within Kubernetes environments and validating enterprise-scale, multi-node distributed systems.
• Scripting automated checks for server-node topology, PCIe link speeds, HBM memory status, firmware performance, and interfacing with hardware via BMC, IPMI, or Redfish.
• Demonstrated capability integrating automated infrastructure validation suites into CI/CD pipelines.
• Configuring observability pipelines for real-time diagnostic logs and hardware metrics.
• History of partnering across Engineering, Product, and Datacentre Operations to conduct root-cause analysis on complex platform regressions and hardware-software boundaries.

Preferred Experience:

• Prior experience validating infrastructure specifically optimized for massive model-training workloads, including a solid understanding of GPU-to-CPU process affinity and master-to-worker rendezvous routing.
• Deep understanding of high-throughput network fabrics, traffic patterns, and congestion control parameters in multi-node GPU clusters.
• Background in building and executing cluster-level benchmarking suites and high-performance storage benchmarks to isolate node-to-node throughput limits.
• Experience designing intelligent test systems capable of autonomously detecting environment drifts and analysing large-scale platform changes.

Why Join Era4:

You’ll be joining a mission-driven start-up building critical national infrastructure, where operational excellence directly enables growth. This role offers high visibility with leadership, real autonomy, and the chance to shape how a next-generation company operates at scale.

Diversity & Inclusion:

Era4 is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.