At a Glance
- Tasks: Build and maintain a shared Python platform for AI document processing.
- Company: Join a leading tech firm in Edinburgh with a hybrid work model.
- Benefits: Competitive market rate, flexible working, and a chance to work on innovative projects.
- Other info: Great opportunity for career growth and working alongside experienced AI Engineers.
- Why this job: Make an impact by developing cutting-edge AI solutions in a collaborative environment.
- Qualifications: Strong Python skills, experience with Kubernetes, and cloud infrastructure knowledge.
The predicted salary is between 50000 - 60000 £ per year.
A Harvey Nash client is seeking a strong Python Engineer to support the build and operation of a shared AI platform focused on document processing (including extraction and transcription use cases). You'll work alongside two experienced AI Engineers, owning the core engineering platform that underpins model delivery. This is a platform/software engineering role, not data science - focused on building production-grade Python services, workflow orchestration, and cloud infrastructure.
Key Responsibilities
- Build and maintain a shared Python platform library (config, logging, telemetry, Azure integrations, model abstractions)
- Develop and run Temporal-based workflows for document processing pipelines
- Implement and manage model-serving within Kubernetes workloads
- Own infrastructure-as-code (Terraform) and GitOps deployments (ArgoCD)
- Deploy and operate services on AKS (autoscaling, containers, service mesh)
- Deliver observability (Prometheus, Grafana, App Insights) and support automation
- Ensure data quality, validation, and integration with enterprise systems
- Collaborate across engineering teams and produce clear documentation
Required Experience
- Strong production Python (typed, tested, well-structured code)
- Kubernetes and containerised workloads in production
- Terraform (or equivalent IaC) and CI/CD / GitOps pipelines
- Azure platform experience (AKS, Service Bus, Postgres, Key Vault, etc.)
- Observability tooling (metrics, logs, alerting)
- Experience supporting services end-to-end in production
- Familiarity working alongside AI/ML workloads (non-data science focus)
Desirable
- Temporal.io or similar workflow tools
- LLM serving (e.g. vLLM) or GPU workloads on Kubernetes
- ArgoCD, KEDA, service mesh (Istio etc.)
- Exposure to regulated/public sector environments
Please note that you must be eligible for BPSS Clearance to commence this post.
Locations
Python Engineer in Edinburgh, Scotland employer: Harvey Nash
Join a forward-thinking company in Edinburgh that values innovation and collaboration, offering Python Engineers the chance to work on cutting-edge AI platforms. With a hybrid work model, competitive rates, and a strong focus on employee growth through mentorship and skill development, this role provides a unique opportunity to contribute to impactful projects while enjoying a supportive work culture. The company's commitment to excellence ensures that you will be part of a team that prioritises quality and continuous improvement in a dynamic environment.
StudySmarter Expert Advice🤫
We think this is how you could land Python Engineer in Edinburgh, Scotland
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech world, especially those who work with Python or AI. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a GitHub repository showcasing your Python projects, especially any related to cloud infrastructure or document processing. This gives potential employers a taste of what you can do before they even meet you.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with Kubernetes, Terraform, and Azure. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Python Engineer in Edinburgh, Scotland
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Python Engineer role. Highlight your experience with production-grade Python services, Kubernetes, and any relevant cloud infrastructure work. We want to see how your skills match what we're looking for!
Showcase Your Projects:Include specific projects that demonstrate your expertise in building and maintaining Python platforms. If you've worked with Terraform or Azure, let us know! Real-world examples can make your application stand out.
Keep It Clear and Concise:When writing your application, clarity is key. Use straightforward language and avoid jargon unless it's relevant to the role. We appreciate a well-structured application that gets straight to the point!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and we’ll be able to review your application more efficiently. Don’t miss out on this opportunity!
How to prepare for a job interview at Harvey Nash
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss your experience with production-grade Python code, including how you've structured and tested it. They’ll likely want to hear about specific projects where you’ve built or maintained Python services.
✨Familiarise Yourself with Kubernetes
Since this role involves working with Kubernetes and containerised workloads, it’s crucial to understand how these technologies work. Prepare to talk about your hands-on experience with deploying and managing applications in a Kubernetes environment, and be ready to share any challenges you faced and how you overcame them.
✨Show Off Your Infrastructure Skills
This position requires knowledge of infrastructure-as-code tools like Terraform. Be prepared to discuss your experience with CI/CD pipelines and GitOps deployments. Highlight any specific examples where you’ve successfully implemented these practices in previous roles.
✨Demonstrate Collaboration and Documentation Skills
Collaboration is key in this role, so think of examples where you’ve worked effectively with other engineering teams. Also, be ready to discuss how you approach documentation, as clear communication is essential for maintaining a shared platform library.
