Software Engineer ( Python

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.

• 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.
• 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
  .