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.