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For Companies At a Glance
- Tasks: Build and operate data infrastructure for innovative products and AI capabilities.
- Company: Join a forward-thinking tech company with a collaborative culture.
- Benefits: Enjoy competitive salary, flexible work, ongoing training, and volunteer days.
- Why this job: Make a real impact by developing cutting-edge software and AI features.
- Qualifications: Experience in cloud-based systems and strong programming skills required.
- Other info: Dynamic team environment with excellent growth opportunities in AI and data.
The predicted salary is between 36000 - 60000 £ per year.
We’re looking for a Software Engineer to help build and operate the data infrastructure that powers our next generation of products and AI-driven capabilities. In this role, you’ll take ownership of observability, monitoring, and reliability across our platform, ensuring every feature is measurable, performant, and resilient from day one.
Alongside infrastructure and operations work, you’ll contribute directly to our software codebase, developing data-driven services and AI-integrated features. This is a hands-on engineering role for someone who enjoys automation, problem solving, and building scalable systems while growing into data and AI technologies. This is a hybrid role requiring 3 days per week in our Newcastle office.
First 90 Days
- 30 days: Get familiar with our platform architecture, data pipelines, monitoring tools, and cloud environment. Understand existing observability practices, alerting systems, and software development workflows.
- 60 days: Begin actively improving logging, performance tracking, and cost monitoring across services. Contribute code to internal products and data-driven applications while tuning alerting systems for clarity and reliability.
- 90 days: Own observability standards for new features and pipelines. Lead root-cause investigations using monitoring data and implement long-term fixes through automation and code improvements. Drive continuous improvements in reliability, performance, and cost efficiency.
Meet the Team
You’ll work closely with software engineers, data engineers, product teams, and AI specialists in a collaborative, fast-moving environment. The team values automation, operational excellence, and building systems that scale reliably while enabling rapid product innovation.
How Success Will Be Measured
- Consistent implementation of observability across all new services and features
- Improved system reliability, performance, and actionable alerting
- Early detection and resolution of cost anomalies in cloud usage
- Quality and maintainability of code contributions to data and AI-enabled products
- Reduction in recurring incidents through strong root-cause analysis and preventative solutions
Skills You’ll Gain
- Deep expertise in observability, monitoring, and cloud cost management
- Hands-on experience building data-driven and AI-enabled software products
- Strong exposure to automation and reliability engineering practices
- Experience working across infrastructure, software development, and operations
- Growth into AI/ML-adjacent systems and data platform engineering
Snapshot of Your Day-to-Day
- You’ll integrate logging, metrics, and performance tracking into new services and pipelines.
- You’ll monitor platform health, investigate anomalies, and fine-tune alerting systems to remain accurate and actionable.
- You’ll track cloud usage and identify cost spikes, working with the team to optimise infrastructure.
- You’ll contribute code to internal tools, data platforms, and AI-integrated features.
- You’ll lead root-cause analysis for incidents and implement long-term fixes through automation and system improvements.
Must-Have Skills
- Experience as a Software Engineer working on cloud-based or data-driven systems
- Strong programming skills with a focus on clean, maintainable code
- Experience implementing monitoring, logging, and observability solutions
- Familiarity with cloud platforms and cost management concepts
- Understanding of software development lifecycles and operational best practices
- Strong problem-solving mindset with a focus on reliability and automation
- Ability to work effectively in cross-functional teams
- Excellent communication skills in English
Nice-to-Have Skills
- Experience with data pipelines, analytics platforms, or AI-integrated systems
- Familiarity with incident response, SRE, or reliability engineering practices
- Exposure to automation tools, infrastructure as code, or DevOps workflows
- Interest or experience in AI/ML systems and data infrastructure
At Sage, we offer you an environment where you can grow professionally without compromising your personal well-being. Our benefits package is designed to provide stability, flexibility, and balance:
- Work away scheme for up to 10 weeks a year
- On-going training and professional development
- Paid 5 days yearly to volunteer through our Sage Foundation
- Flexible work patterns and hybrid working
Software Engineer (AWS) in Newcastle upon Tyne employer: Sage
Contact Detail:
Sage Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software Engineer (AWS) in Newcastle upon Tyne
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or at meetups. Ask them about their experiences and the company culture. This can give you insider info and might even lead to a referral!
✨Tip Number 2
Prepare for those technical interviews! Brush up on your coding skills and be ready to discuss your past projects. Practice common algorithms and data structures, and don’t forget to showcase your problem-solving mindset.
✨Tip Number 3
Show off your passion for automation and AI! During interviews, share examples of how you've implemented these in your previous roles. It’ll demonstrate that you’re not just a coder, but someone who’s keen on innovation.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team and contributing to our exciting projects.
We think you need these skills to ace Software Engineer (AWS) in Newcastle upon Tyne
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Software Engineer role. Highlight your experience with cloud-based systems, observability, and any relevant projects you've worked on. We want to see how you can contribute to our data-driven products!
Craft a Compelling Cover Letter: Your cover letter is your chance to show us your personality and passion for the role. Share why you're excited about working with AI technologies and how your problem-solving mindset aligns with our team's goals. Keep it engaging and let your enthusiasm shine through!
Showcase Your Projects: If you've worked on any relevant projects, whether personal or professional, make sure to mention them in your application. We love seeing hands-on experience, especially with automation and reliability engineering practices. It gives us a glimpse of what you can bring to the table!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It streamlines the process and ensures your application reaches the right people. Plus, it shows us you're keen on joining our team at StudySmarter!
How to prepare for a job interview at Sage
✨Know Your Stuff
Before the interview, dive deep into the company's platform architecture and data pipelines. Familiarise yourself with their monitoring tools and observability practices. This will not only show your genuine interest but also help you answer technical questions confidently.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled challenges in cloud-based or data-driven systems. Highlight your experience with automation and reliability engineering, as these are key aspects of the role. Use the STAR method (Situation, Task, Action, Result) to structure your responses.
✨Communicate Clearly
Since you'll be working closely with cross-functional teams, practice explaining complex technical concepts in simple terms. Good communication skills are essential, so be ready to demonstrate how you can convey ideas effectively during the interview.
✨Ask Insightful Questions
Prepare thoughtful questions about the team's current projects, challenges they face, and their approach to observability and performance tracking. This shows that you're not just interested in the job, but also in contributing to the team's success and growth.
