Senior Security Consultant (Cloud Security)

Claranet
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Science Consultant

Senior Data Science Consultant

Senior Data Scientist

Senior Data Scientist

Senior Data Specialist

Senior DataOps Engineer

About The Role

Essential duties & responsibilities

Support the development and execution of an enterprise-wide Cloud security program. Define and manage security controls for a multi-cloud architecture. Configure, maintain, deploy, and craft intricate rules within the framework of Cloud security tools, exhibiting a nuanced understanding of their functionality. Design and implement 3rd party as well as cloud-native tooling, aligning them meticulously with predefined requirements to optimize security measures. Develop standard operating procedures and conduct comprehensive training sessions for each technology, ensuring a thorough understanding and adherence to best practices. Configure, maintain, deploy, and write rules in Cloud security tools. Design and implement 3rd party and cloud-native tooling to meet defined requirements. Develop standard operating procedures and training for each technology. Architect and continuously improve security technology stack, process and procedures, support model and cross-function interactions utilizing automation where possible. Collaborate with the Security Operations team to swiftly respond to cybersecurity incidents, demonstrating a united front against potential threats. Review and assess utilization of Cloud security tooling. Promote and drive adoption of Cloud security tooling across the enterprise. Partner across the Security Operations team to respond to cybersecurity incidents. Develop and report Cloud security coverage metrics and remediation plans. Define procedures to validate the effectiveness of the design, deployment, and management of security controls that aim to maintain confidentiality, integrity, and availability of Cloud networks and technology platforms. Conduct research to stay up to date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services. Experience contributing to the system design (architecture, design patterns, reliability, and scaling) of new and current cloud-based GenAI services. Conduct thorough reviews and assessments of the utilization of Cloud security tooling, ensuring optimal performance and alignment with security objectives. Configure, maintain, deploy, and craft intricate rules within the framework of Cloud security tools, exhibiting a nuanced understanding of their functionality.

About You

Position specifications

Bachelor’s Degree or industry equivalent work experience in cybersecurity, international security architecture, and/or engineering in a converged security program 4-7 years of experience operating with at least one cloud provider, preferably GCP, Azure, or AWS Strong understanding of Cloud security industry standards and best practices (CSA CCM, CIS, NIST benchmarks, etc.) Proficient use of Linux, MacOS, and Windows Operating System tools Operating and maintaining tools across the Cloud security technology stack (CSPM, CWPP, SASE, CASB, CIEM, Cloud native features like GuardDuty, AWS Config, Amazon Inspector, etc.) Conversant with Cloud security technology stack, encompassing CSPM, CWPP, SASE, CASB, CIEM, and Cloud-native features such as GuardDuty, AWS Config, Amazon Inspector, and more. Ability to visualize and integrate cloud-specific data and alerts with other security systems. experience in a multi-cloud or hybrid cloud environment, demonstrating adaptability across diverse technological landscapes. hands-on experience in utilizing one or more programming/scripting languages, such as Python, Go, Java, Terraform, etc. Experience in a multi-cloud or hybrid-cloud environment Working knowledge of SecDevOps and proficiency in embracing Shift Left concepts to enhance security measures throughout the development lifecycle. Technical knowledge of Kubernetes and Docker technologies and associated security requirements (Kubernetes, Docker, etc.) Experience contributing to the system design (architecture, design patterns, reliability, and scaling) of new and current cloud-based GenAI services. Familiarity with source code management and proficiency in CI/CD tools, such as Github, Bitbucket, Jenkins, Artifactory, etc. Should have at least one associate-level cloud certification, such as AWS Solutions Architect GCP Associate Cloud Engineer, as a testament to specialized knowledge and expertise.

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.

Top 10 Mistakes Candidates Make When Applying for AI Jobs—And How to Avoid Them

Avoid the biggest pitfalls when applying for artificial intelligence jobs. Discover the top 10 mistakes AI candidates make—plus expert tips and internal resources to land your dream role. Introduction The market for AI jobs in the UK is booming. From computer-vision start-ups in Cambridge to global fintechs in London searching for machine-learning engineers, demand for artificial-intelligence talent shows no sign of slowing. But while vacancies grow, so does the competition. Recruiters tell us they reject up to 75 per cent of applications before shortlisting—often for mistakes that could have been fixed in minutes. To help you stand out, we’ve analysed thousands of recent applications posted on ArtificialIntelligenceJobs.co.uk, spoken with in-house talent teams and independent recruiters, and distilled their feedback into a definitive “top mistakes” list. Below you’ll find the ten most common errors, along with actionable fixes, keyword-rich guidance and handy internal links to deeper resources on our site. Bookmark this page before you hit “Apply”—it could be the difference between the “reject” pile and a career-defining interview.

Top 10 Best UK Universities for AI Degrees (2025 Guide)

Discover the ten best UK universities for Artificial Intelligence degrees in 2025. Compare entry requirements, course content, research strength and industry links to choose the right AI programme for you. Artificial Intelligence continues to transform industries—from healthcare to finance to transportation. The UK leads the way in AI research and education, with several universities consistently ranked among the world’s best for Computer Science. Below, we spotlight ten UK institutions offering strong AI-focused programmes at undergraduate or postgraduate level. While league tables shift year to year, these universities have a track record of excellence in teaching, research, and industry collaboration.

How to Write a Winning Cover Letter for AI Jobs: Proven 4-Paragraph Structure

Learn how to craft the perfect cover letter for AI jobs with this proven 4-paragraph structure. Perfect for junior developers and career switchers. When applying for an AI job, your cover letter can make all the difference. For many, the process of writing a cover letter for an AI position can be daunting, especially when there are so few specific guides for tailoring it to the industry. However, a clear, effective structure combined with AI-specific language and examples can help you stand out from the competition. Whether you're a junior entering the field or a mid-career professional switching to AI, the following framework will make it easier for you to craft a compelling cover letter. In this article, we’ll take you through a proven four-paragraph structure that works and provide sample lines that you can adapt to your personal experience.