At a Glance
- Tasks: Own the infrastructure strategy and improve pipelines for cutting-edge tech solutions.
- Company: Join Kodamai, a forward-thinking tech company with a focus on innovation.
- Benefits: Enjoy competitive pay, flexible remote work, and opportunities for professional growth.
- Other info: Dynamic role with excellent career advancement potential in a collaborative environment.
- Why this job: Make a real impact by shaping the future of technology and client solutions.
- Qualifications: Experience in GCP, DevOps practices, and strong problem-solving skills.
The predicted salary is between 60000 - 80000 £ per year.
As a Senior DevOps/MLOps Engineer at Kodamai, you will own the end-to-end infrastructure strategy, from setting up and maintaining our GCP-based internal environments to advising clients on optimal deployment architectures. You will design, implement, and continuously improve the pipelines and platforms that underpin both Kodamai's core technology and the solutions we build for clients.
Key Responsibilities
- GCP Infrastructure & Internal Dev Environments
- Design, provision, and manage GCP infrastructure (GKE, Cloud Run, Compute Engine, Cloud Storage, VPC, IAM) for Kodamai's core technology platform.
- Build and maintain internal development environments for client project teams, ensuring reliability, security, and cost efficiency.
- Define infrastructure-as-code (IaC) standards across all environments.
- Implement robust monitoring, alerting, and logging using GCP-native tools (Cloud Monitoring, Cloud Logging) and third-party stacks (Prometheus, Grafana).
- Client Deployment Advisory & Requirements Analysis
- Engage with clients to analyze their existing deployment infrastructure and constraints.
- Provide tailored recommendations on deployment strategies, tooling, and architecture patterns that integrate seamlessly with their current environment.
- Produce technical assessments and deployment architecture proposals as part of pre-sales and onboarding processes.
- Act as a trusted technical advisor to client engineering teams during implementation and go-live phases.
- Design and implement end-to-end CI/CD pipelines.
- Establish branching strategies, release management processes, and deployment gating (automated testing, security scans, approvals).
- Ensure high pipeline reliability, fast feedback loops, and clear rollback mechanisms.
- Champion DevOps best practices across engineering teams - documentation, runbooks, and post-mortems.
- MLOps
- Support the operationalization of ML models - model versioning, experiment tracking, and deployment workflows.
- Work with data science teams to configure MLOps tooling such as Vertex AI, MLflow, Kubeflow, or similar platforms.
- Enable automated model retraining, drift detection, and performance monitoring pipelines.
Senior DevOps / MLOps Engineer in Glasgow employer: Kodamai Limited
At Kodamai, we pride ourselves on being an exceptional employer, offering a collaborative and growth-oriented work environment that empowers our engineers to thrive. With competitive consultancy fees and continuous learning opportunities in cutting-edge AI technologies, our remote team enjoys the flexibility to innovate while contributing to impactful projects. Join us in shaping the future of autonomous workflows and experience a culture that values teamwork, creativity, and professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Senior DevOps / MLOps Engineer in Glasgow
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that dream role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving GCP and CI/CD pipelines. We want to see what you can do, so make it easy for potential employers to check out your work.
✨Tip Number 3
Prepare for interviews by practising common DevOps scenarios. We recommend running through some mock interviews with friends or using online platforms. The more you practice, the more confident you'll feel when it’s showtime!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior DevOps / MLOps Engineer in Glasgow
Some tips for your application 🫡
Show Off Your Skills:When you're writing your application, make sure to highlight your experience with GCP and any relevant tools you've used. We want to see how you can bring your expertise to our team!
Tailor Your Application:Don’t just send a generic application! Take the time to tailor your CV and cover letter to reflect the specific responsibilities mentioned in the job description. It shows us you’re genuinely interested in the role.
Be Clear and Concise:Keep your application clear and to the point. Use bullet points for your achievements and experiences, so we can quickly see what you bring to the table. We love a well-structured application!
Apply Through Our Website:Make sure to apply through our website! It’s the best way for us to keep track of your application and ensures you don’t miss out on any important updates from us.
How to prepare for a job interview at Kodamai Limited
✨Know Your GCP Inside Out
Make sure you’re well-versed in GCP services like GKE, Cloud Run, and Compute Engine. Brush up on how to design and manage infrastructure-as-code (IaC) standards, as this will likely come up during your interview.
✨Showcase Your CI/CD Expertise
Be prepared to discuss your experience with CI/CD pipelines. Highlight specific examples where you've implemented branching strategies or automated testing, and how these improved deployment reliability and speed.
✨Engage with Client Scenarios
Think of a few client scenarios where you had to analyse deployment constraints and provide tailored recommendations. This will demonstrate your ability to act as a trusted advisor and your understanding of client needs.
✨Demonstrate MLOps Knowledge
Familiarise yourself with MLOps tools like Vertex AI and MLflow. Be ready to discuss how you’ve operationalised ML models and the importance of model versioning and performance monitoring in your previous roles.
