What You'll Do:

🔧 Bridge Data Science and Production: Take pricing and demand models from experimentation to live, reliable production systems.

🏗 Build the Serving Layer: Design and maintain the APIs and infrastructure that deploy models into the real world.

⚡ Own the Pipelines: Keep data flowing reliably from source to model to output, with monitoring and alerting built in from the start.

🔍 Drive Operational Excellence: Implement automated testing, observability, and monitoring across the team's production systems.

🤝 Work Cross-Functionally: Partner daily with Data Scientists, Analysts, and Engineering to turn prototypes into production-ready solutions.

The Team:

You'll join a small, newly formed team inside a much larger engineering organisation, with a clear mission: help drive smarter, data-driven pricing decisions across the business. It's a team that cares about impact, collaboration, and learning together, using modern tooling and genuine AI-native workflows day to day.

What They're Looking For:

• 4+ years of experience in Software Engineering, Data Engineering, DevOps, or MLOps
• Strong hands-on Python, writing clean, production-quality code
• Experience with CI/CD, Docker, and infrastructure-as-code such as Terraform
• Familiarity with cloud platforms, AWS preferred, and deploying services into production
• Exposure to or interest in ML model deployment, tools like MLflow or SageMaker are a strong plus
• A proactive, hands-on mindset, someone who spots problems and drives solutions forward
• Genuine appetite for using cutting-edge LLM tools and agents to boost your own and the team's productivity
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