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 - 65000 £ 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 Dunfermline 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 culture.
StudySmarter Expert Advice🤫
We think this is how you could land Python Engineer in Dunfermline
✨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 and soft skills. Practice coding challenges and be ready to discuss your past projects, especially those involving Kubernetes and Terraform. 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, it’s super easy to keep track of your applications!
We think you need these skills to ace Python Engineer in Dunfermline
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 knowledge of typed and tested 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 specific projects where you’ve deployed services or managed workloads.
✨Showcase Your Infrastructure Skills
This position requires a solid grasp of infrastructure-as-code tools like Terraform. Make sure you can explain how you've used Terraform or similar tools in past projects. Discussing your experience with CI/CD pipelines and GitOps will also show that you’re well-versed in modern deployment practices.
✨Demonstrate Collaboration and Documentation Skills
Collaboration is key in this role, so be ready to share examples of how you’ve worked with other engineering teams. Highlight your ability to produce clear documentation, as this will be essential for maintaining the shared Python platform library and ensuring smooth operations across teams.
