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 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 familiarity with Azure.
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.
Python Engineer in Broughton employer: Harvey Nash
Join a forward-thinking company in Edinburgh that values innovation and collaboration, offering a dynamic work culture where your contributions as a Python Engineer will directly impact the development of cutting-edge AI solutions. With a strong emphasis on employee growth, you will have access to continuous learning opportunities and the chance to work alongside experienced professionals in a hybrid environment that promotes work-life balance. Enjoy competitive rates and the unique advantage of being part of a team that is at the forefront of technology in a vibrant city known for its rich history and thriving tech scene.
StudySmarter Expert Advice🤫
We think this is how you could land Python Engineer in Broughton
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with online communities. We all know that sometimes it’s not just what you know, but who you know that can help you land that Python Engineer role.
✨Tip Number 2
Show off your skills! Create a GitHub repository showcasing your Python projects, especially those related to AI or cloud infrastructure. This gives potential employers a taste of your coding style and problem-solving abilities, making you stand out from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python knowledge and Kubernetes experience. We recommend doing mock interviews with friends or using platforms that simulate real interview scenarios. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, we love seeing passionate candidates who are eager to join our team!
We think you need these skills to ace Python Engineer in Broughton
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 where you've built or maintained Python platforms or worked with AI/ML workloads. This gives us a clear picture of your hands-on experience and how you can contribute to our shared AI platform.
Be Clear and Concise:When writing your application, keep it clear and to the point. Use bullet points for key achievements and responsibilities. We appreciate straightforward communication that gets right to the heart of your experience.
Apply Through Our Website:Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it makes the whole process smoother for everyone involved.
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 services, and don’t shy away from showcasing your well-structured code. Practising coding challenges can also help you demonstrate your problem-solving abilities.
✨Familiarise Yourself with Kubernetes
Since this role involves working with Kubernetes and containerised workloads, it’s crucial to understand how they operate in a production environment. Be prepared to talk about your hands-on experience with Kubernetes, including any challenges you've faced and how you overcame them.
✨Show Off Your Infrastructure Skills
This position requires knowledge of infrastructure-as-code tools like Terraform. Make sure you can explain how you've used Terraform or similar tools in past projects. Discuss your experience with CI/CD pipelines and GitOps deployments, as these are key components of the role.
✨Communicate Clearly and Collaboratively
Collaboration is key in this role, so be ready to discuss how you've worked with other engineering teams in the past. Highlight your ability to produce clear documentation and ensure data quality. Good communication skills will set you apart, so practice articulating your thoughts clearly.
