Senior Site Reliability Engineer – DevOps

LogicMonitor
London
3 weeks ago
Create job alert

What You'll Do:

LM Envision, LogicMonitor's leading hybrid observability platform powered by AI, helps modern enterprises gain operational visibility into and predictability across their IT stacks, so they can continue to deliver extraordinary employee and customer experiences. LogicMonitor has a layered approach to intelligence, where AI and Machine Learning is baked into every facet of the LM Envision platform to help IT teams improve efficiency, minimise alert fatigue, proactively predict trends, and maximise enterprise growth and transformation. 

Our customers love LogicMonitor's ability to bring cloud and traditional IT together into one view, as seen in minimal churn rates, expansion business, and exciting new customer references. In fact, LogicMonitor has received the highest Net Promoter Score of any IT Infrastructure Management provider. LogicMonitor also boasts high employee satisfaction. We have been certified as a Great Place To Work®, and named one of BuiltIn's Best Places to Work for the sixth year in a row! 

This role will take a lead in the operational uptime and continued expansion of LM Edwin AI infrastructure by serving as a facilitator of operational excellence. Responsibilities include designing and implementing new production deployments of SOA-based software across cloud datacentres, as well as providing guidance on organizing, securing and automating existing infrastructure and deployments. This position involves working with developers and providing feedback to drive operational performance improvements within the LM platform and operations infrastructure.

Here's a closer look at this key role:

Maintain uptime of LogicMonitor's (Edwin AI) SaaS-based service and drive technical/process enhancements to improve uptime. Lead efforts to design and implement resilient IT applications using DevOps and SRE principles. Deploy production applications and drive improvements to the deployment process. Monitor system performance and troubleshoot issues to ensure high availability and reliability. Design and deploy new application components . Design and deploy new infrastructure components and integrations. Ensure security of the production environment. Develop and implement automated disaster recovery processes to minimise system downtime. Identify opportunities for improvement in system performance, deployment speed, and scalability. Write high-quality code to automate various aspects of infrastructure maintenance and and deployment. Support engineering and work closely with engineers to drive operational and architectural/design changes. Own, manage, and execute multiple large and technically complex projects across teams. Providing alignment between business objectives and the team's pursuit of technology improvements. Contribute to remediation actions relating to service disruptions and outages. Provide direct technical guidance to help team members achieve goals and improve their productivity. Participate in the recruitment and hiring of new engineers.

What You'll Need:5+ years as a DevOps Engineer or SRE with designing and implementing resilient IT applications using DevOps and SRE principles. Good understanding of Linux system administration and 3+ years of hands-on experience. Good understanding of networking technologies. Experience building IaC automations using Terraform. Production experience of containers and container orchestration tools (Docker/Kubernetes). Good understanding of Amazon Web Services Experience of designing/implementing CI/CD pipelines including production deployments. Experience building and working with logging and metrics solutions such as Prometheus. Experience programming with RESTful web services. Proficient Python developer. Well-versed in security principles, both systems and network. Excellent written and verbal communications skills with a track record of improving documentation and processes. Experience is carrying out complex problem determination and Root Cause Analysis across complex distributed systems.

Click to read our International Applicant Privacy Notice.

LogicMonitor is an Equal Opportunity Employer
At LogicMonitor, we believe that innovation thrives when every voice is heard and each individual is empowered to bring their unique perspective. We’re committed to creating a workplace where diversity is celebrated, and all employees feel inspired and supported to contribute their best.

For us, equal opportunity means fostering a truly inclusive culture where everyone has the chance to grow and succeed. We don’t just open doors; we invite you to step through and be part of something bigger. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

#LI-KW1 #BI-Hybrid #LI-Hybrid

Related Jobs

View all jobs

Site Reliability Engineer

Senior Electrical Project Engineer

Senior Electrical Project Engineer

Design & Development Engineer (Hardware)

Senior Data Analyst

Senior Content Designer

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.

Careers

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Jobs

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.

Careers

Career Paths in Machine Learning: From Entry-Level Roles to Leadership and Beyond

Machine learning has rapidly transformed from an academic pursuit to a cornerstone of modern technology, fueling innovations in healthcare, finance, retail, cybersecurity, and virtually every industry imaginable. From predictive analytics and computer vision to deep learning models that power personalisation algorithms, machine learning (ML) is reshaping business strategies and creating new economic opportunities. As demand for ML expertise continues to outstrip supply, the UK has become a vibrant hub for machine learning research, entrepreneurship, and corporate adoption. Whether you’re just starting out or have experience in data science, software development, or adjacent fields, there has never been a better time to pursue a career in machine learning. In this article, we will explore: The growing importance of machine learning in the UK Entry-level roles that can kick-start your ML career The skills and qualifications you’ll need to succeed Mid-level and advanced positions, including leadership tracks Tips for job seekers on www.machinelearningjobs.co.uk By the end, you’ll have a clear view of how to build, grow, and lead in one of the most exciting fields in modern technology.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.