Senior Threat Detection Engineer (Cyber Security)

Centrica
Leeds
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Scientist (UK Remote)

Senior Machine Learning Scientist (UK Remote)

Senior Director Artificial Intelligence/Machine Learning

Data Science Manager

Senior/Principal Data Scientist – Cross Indication

Join us, be part of more. 

We’re so much more than an energy company. We’re a family of brands revolutionising how we power the planet. We're energisers. One team of 21,000 colleagues that's energising a greener, fairer future by creating an energy system that doesn’t rely on fossil fuels, whilst living our powerful commitment to igniting positive change in our communities. Here, you can find more purpose, more passion, and more potential. That’s why working here is #MoreThanACareer. We do energy differently - we do it all. We make it, store it, move it, sell it, and mend it.

About your team: 

You’ll be working centrally within our mission control room, aka Centrica’s group functions. From Finance and Data Science, to our Wellbeing and People teams - this is the engine of our energy system, where our various Centres of Excellence power up each of our brilliant businesses, ensuring they have all the support, technologies, and capabilities they need to get our customers to Net Zero by 2050.

Join Centrica's IT Security Team as a Senior Threat Detection Engineer!

Are you ready to play your part in driving the UK's energy transformation? Centrica is looking for a passionate and skilledSeniorThreat Detection Engineer (Cyber Security)to join our dynamic IT Security team. If you're excited about developing, automating, and improving detection capabilities to effectively identify and respond to security threats, this is the perfect opportunity for you!

Location:Remote working with occasional travel to our Windsor office.

Key Responsibilities:

Implement and manage the Detection Engineering framework across our infrastructure.

Develop and maintain consistent, scalable, and effective detection capabilities.

Continuously assess and improve detection logic and use cases.

Automate detection engineering workflows using GitOps and CI/CD principles.

Build and optimize security playbooks for detection, threat hunting, and incident response.

Enhance threat detection and response capabilities, including Azure Logic Apps.

Collaborate with security analysts and stakeholders to address incident response gaps.

Stay updated on current threat intelligence, trends, TTPs, and vulnerabilities.

Skills Required:

Experience with detection rules (KQL) and frameworks like MITRE ATT&CK.

Proficiency in PowerShell, Python, or Go for security use cases.

Hands-on experience with infrastructure as code tools (Terraform, Ansible, Puppet).

Strong understanding of Azure and AWS cloud platforms.

Familiarity with GitOps concepts and CI/CD workflows.

Experience with security automation platforms (SOAR) and orchestration playbooks.

Background in Security Operations and Cyber Security Incident Response.

Education:

Bachelor’s degree preferred (but not essential) in IT, Computer Science, Information Systems, or related field. Relevant experience will be considered in lieu of qualifications.

Why Join Us?

Be part of a team that supports sustainable energy solutions and delivers impactful projects. Your contributions will make a real difference!

Benefits:

Competitive salary and bonus potential.

Car allowance

Employee Energy Allowance at 15% of the government price cap.

Pension scheme.

Company-funded healthcare plan.

25 days holiday allowance, plus public holidays, with the option to buy up to 5 additional days.

A range of flexible benefits, including technology vouchers, an electric car lease scheme, and travel insurance.

Ready to make an impact? Apply now and join us in shaping the future of energy!

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.