Cloud Security Engineer

ABOUT UNIVERS

Univers combines global operating scale, deep industrial intelligence, and recognition from the institutions shaping energy, technology, and sustainability. The platforms built for the last decade were designed to monitor.

Univers was built to act - not just report

Univers operates at global scale:

1,070 GW+ Energy assets under AI management 450M+ Connected sensors and devices 800+ Enterprise customers Leader Gartner Magic Quadrant Leader ROLE OVERVIEW / THE OPPORTUNITY

As a Cloud Security Engineer who enjoys hands-on security work, you will be the technical backbone of cloud and platform security at Univers, operating as a high-leverage individual contributor across a primarily Microsoft Azure environment with Google Cloud (GCP) security tooling in the mix.

In this role, you will review architectures and implementations from a security perspective and uncover subtle issues that surface under unexpected threat scenarios. You will treat automation as the default and use AI as a force multiplier, applying AI-assisted tooling to triage, detect, and respond at a scale far beyond a traditional one-person team.

You will also stand up and operate the security tooling that protects Univers’ growing portfolio of AI and machine-learning workloads, working alongside vendors to deploy these capabilities and then owning their day-to-day tuning and operation. You will consume threat intelligence and help design a robust, resilient cloud infrastructure and platform for Univers and its customers.

RESPONSIBILITIES/WHAT YOU WILL DO

Consult with stakeholders on security requirements and utilize best practices to meet them Collaborate with the Cloud Infrastructure and Platform teams to lead initiatives and build security utilities, leveraging scripting and AI-assisted automation, that enable Univers to operate more securely with a lean security team Build and tune threat detection across a hybrid, multi-cloud stack (primarily Azure, with GCP) covering application infrastructure, containers and Kubernetes, IoT/OT infrastructure, and AI/ML workloads Contribute to and lead communications with the team and other business units Build and maintain a robust infrastructure/platform security roadmap to meet customer demands and regulatory mandates Develop, maintain, and promote standards through workshops, knowledge shares and brown bags Promotes security and cloud best practices Onboard, develop and operate Security Information and Event Management (SIEM) and Security Orchestration, Automation and Response (SOAR) capabilities, including AI-assisted detection, alert triage and automated response playbooks

Deploy, configure and operate security tooling for Univers’ AI/ML and large language model (LLM) workloads, working with vendors during deployment and owning ongoing tuning, monitoring and maintenance

Secure AI systems against AI-specific threats (e.g. prompt injection, data and model exfiltration, insecure agent/tool permissions) and apply recognised guidance such as the OWASP Top 10 for LLM Applications and the relevant MITRE ATLAS techniques

Govern identity and access for both human and non-human identities, including service principals, workload identities and AI agents, enforcing least privilege across the Azure and GCP estate

Support the enterprise AI governance agenda by translating policy into enforceable technical controls and providing assurance over how AI is built, deployed and used securely REQUIREMENTS/WHAT WE ARE LOOKING FOR

Azure security certification (e.g. AZ-500/SC-100) required or strongly preferred; GCP Professional Cloud Security Engineer and AWS security certifications are a plus

At least 5+ years of hands-on cloud security experience, with deep, demonstrable expertise in Microsoft Azure security and working knowledge of Google Cloud (GCP) security tooling

Strong knowledge of network security including Firewall and WAF

Strong knowledge of identity and access management and identity federation (SAML, OAuth 2.0, OIDC), including Microsoft Entra ID and the management of non-human / workload identities

Experience designing and implementing security controls in cloud platforms (Azure primarily, GCP and similar), including CSPM/CNAPP tooling such as Microsoft Defender for Cloud

Experience with the application of risk identification and evaluation techniques

Experience with broad set of information security technologies and processes within a SaaS, IaaS, PaaS, or cloud environment

Experience with at least one SIEM and SOAR platform, including on boarding of log sources and developing automation

Strong scripting and automation skills (primarily Python), with the ability to use AI-assisted coding and security tooling to operate effectively as a lean, high-leverage team

Working understanding of AI/LLM security concepts and threats, such as prompt injection, model and data exfiltration, and agent/tool abuse, and familiarity with frameworks such as the OWASP Top 10 for LLM Applications, MITRE ATLAS or the NIST AI Risk Management Framework

Hands-on experience deploying and operating AI-enabled security tooling (e.g. AI-driven detection and response, security copilots, or AI-assisted SOAR), with the judgement to validate AI output rather than trust it blindly

Self-directed and comfortable operating as the sole security engineer, able to prioritise independently, partner with vendors, and balance hands-on delivery with strategic security improvement