Platform Engineer - Kubernetes - Openshift - Python - AI / ML - 12 month contract - Glasgow Hybrid (3 days onsite)
I am looking for an experienced Platform Engineer to support the design and rollout of a next-generation AI development environment for our international client based in Glasgow.
This role plays a key part in accelerating the adoption of AI technologies across the business, helping to build scalable infrastructure and intelligent tooling to power innovation and automation at scale.
What You'll Be Doing:
Contributing to the architecture and delivery of a innovative AI platform designed to support large enterprise use cases.
Building and managing containerised applications and services running on Kubernetes (OpenShift preferred).
Developing robust, high-performance APIs using frameworks like Flask or FastAPI.
Enabling reliable, secure data handling through engineering best practices across SQL/NoSQL, Kafka, Redis, and cloud-native storage solutions.
Applying your knowledge of asynchronous processing, multithreading, and system performance optimisation in real-world environments.
Integrating telemetry tools such as Grafana, Loki, Prometheus, and Cortex for monitoring and observability.
Implementing CI/CD pipelines (Jenkins) and contributing to GitOps-driven deployment strategies.
Supporting the adoption of AI and ML tooling across product and engineering teams.
Ensuring development aligns with secure coding and data protection principles.
What You'll Bring:
Solid experience as a hands-on software or platform engineer with deep knowledge of Python Flask or Fast API
A good understanding of data engineering principles, data security, and governance.
Expertise in designing, building, and managing large-scale RESTful services.
Knowledge of OAuth2.0 and modern application security protocols.
Familiarity with Agile and DevOps practices in cloud-native environments.
Excellent communication skills and the ability to work with global teams.
A strong interest in AI, especially its practical application to real-world engineering and productivity problems.
Nice to Have:
Experience working with AI/ML platforms, particularly in generative AI or LLM-based systems.
Exposure to ML/ModelOps and AI workflow automation tools.
Practical experience with agent orchestration tools (e.g., LangChain, LangGraph).
Understanding of microservice-based architecture, distributed state management, and advanced cloud deployment strategies (e.g., blue/green deployments).
Hands-on experience with scalable cloud infrastructure in both public and private environments.
Familiarity with Site Reliability Engineering (SRE) principles and tooling.
Why Join?
This is an exciting opportunity to work on innovative AI platform engineering that combines deep technical challenge with meaningful business impact. You'll help shape how AI is used across a global organisation - from foundational tools to transformational applications.
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