Key Responsibilities
* Design, develop, test, and support robust, production-ready software solutions, adhering to modern engineering best practices.
* Build and maintain microservices-based systems, with a strong focus on scalability, resilience, and performance.
* Develop and optimise scalable data pipelines, supporting both batch and streaming workloads, using technologies such as Apache Spark.
* Work extensively with data technologies, leveraging Python and SQL to deliver high-quality analytical and data-driven solutions.
* Lead the design and delivery of data-centric applications, translating complex business and analytical requirements into well-architected technical solutions.
* Implement and integrate large language models (LLMs), including:
* Utilising both proprietary and open-source models
* Fine-tuning models to meet specific business use cases
* Delivering solutions via APIs, such as OpenAI APIs
* Collaborate closely with product managers, data scientists, and engineering peers to shape technical designs and delivery approaches.
* Apply strong problem-solving and analytical skills to diagnose issues, optimise performance, and improve overall system reliability.
* Contribute to architectural decision-making, participate in code reviews, and support the continuous improvement of engineering standards and practices.
Required Skills & Experience
* Demonstrable hands-on experience developing production-grade backend systems.
* Proven experience designing and implementing microservices architectures, ideally within cloud environments.
* Strong background in data engineering, including building and maintaining large-scale data pipelines.
* Advanced proficiency in Python and SQL.
* Practical experience working with large language models, including model fine-tuning and API-based integrations (e.g. OpenAI).
* Experience in solution and system design, particularly for data-driven and analytical platforms.
* Solid understanding of core software engineering principles, including version control, automated testing, and deployment pipelines.
* Excellent analytical thinking and problem-solving skills, with a pragmatic and delivery-focused mindset.
Desirable Skills
* Experience working with major cloud platforms such as AWS, Azure, or GCP.
* Familiarity with containerisation and orchestration technologies (e.g. Docker, Kubernetes).
* Exposure to MLOps practices or deploying AI/ML models into production environments.
* Experience working in agile or fast-paced delivery teams.