Accountabilities

As a DevOps / Platform Engineer, you will be responsible for the reliability, scalability, and continuous improvement of production infrastructure. You will own projects from initial requirements through implementation and delivery, collaborating with engineering colleagues and customers to achieve meaningful results. Your responsibilities will include:

Run, maintain, and scale production cloud infrastructure supporting a platform that processes terabytes of data daily.

Own build, deployment, and release pipelines for Python, C++, and TypeScript applications.

Design, build, and manage production infrastructure for AI agents, incorporating observability, guardrails, and cost controls.

Lead observability practices and incident response activities to maintain platform reliability.

Automate repetitive operational tasks and workflows using AI agents.

Take end-to-end ownership of infrastructure and platform engineering projects, from identifying requirements to delivering solutions.

Manage multiple priorities, including major engineering projects and smaller AI-driven initiatives.

Communicate effectively with engineering teams and customers, ensuring technical issues are understood and resolved.

Identify opportunities to improve infrastructure, engineering processes, and operational efficiency.

Make informed decisions about priorities and adapt quickly to changing requirements while maintaining delivery quality.

Requirements

The ideal candidate is a technically strong, autonomous engineer who combines hands-on cloud infrastructure expertise with a proactive approach to problem-solving. You should be comfortable taking responsibility for complex projects, using AI tools as part of your daily workflow, and delivering results in a collaborative remote environment. The following qualifications and competencies are expected:

Extensive hands-on experience managing production cloud infrastructure using AWS, Microsoft Azure, or Google Cloud Platform (GCP).

Practical experience with Infrastructure as Code (IaC), particularly Terraform or equivalent technologies.

Strong experience with Docker and containerized environments.

Proven ownership of CI/CD pipelines, including build, deployment, and release processes.

Experience implementing and managing observability, incident response, and robust security practices.

Daily, hands-on experience using AI agents and advanced AI models in engineering workflows.

Ability to use LLMs and AI agents independently to learn unfamiliar technologies, navigate new codebases, and manage multiple projects effectively.

Demonstrated ability to own engineering projects from conception through delivery, rather than focusing solely on assigned tickets.

Strong customer focus, including the ability to communicate directly with customers and take responsibility for resolving their problems.

High sense of urgency and sound judgment when reprioritizing work to maximize impact.

Ability to set priorities, make decisions, and deliver results independently without close supervision.

Strong communication and collaboration skills, with the ability to explain technical decisions and implementation approaches clearly.

Growth mindset, openness to constructive feedback, and willingness to rethink existing code or approaches when necessary.

Trustworthy and accountable working style, with strong attention to detail and the ability to identify and communicate problems early.

Availability to work remotely during UK business hours.

Nice to Have

Experience with Microsoft Azure, particularly in cloud migration initiatives and Azure Marketplace integration.

Familiarity with ClickHouse or other data-intensive platforms.

Experience operating LLM or AI agent workloads in production environments.

Scripting experience with Python or Go.

Familiarity with SOC 2, GDPR, or other regulated environments.

Benefits

Fully remote, long-term employment opportunity.

Opportunity to work on an AI-native cybersecurity platform operating at significant data scale.

High degree of autonomy and end-to-end ownership of engineering projects.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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