What You Will Do
Work with engineering leads, architects, product management and delivery partners to understand requirements, clarify technical options and contribute to implementation plans.
Design, develop, test and maintain cloud-native microservices and REST APIs using Python and relevant frameworks such as FastAPI , FastMCP and Temporal.
Contribute to LLM-powered applications and the supporting services used to develop, deploy, observe and operate them.
Integrate data technologies such as PostgreSQL, Redis and Elasticsearch, following established patterns for performance, reliability and maintainability.
Deliver assigned features or components through design, implementation, code review, testing, deployment and production monitoring, seeking guidance for complex or unfamiliar work.
Investigate and resolve defects in distributed systems using structured analysis, logs, metrics and appropriate debugging tools.
Contribute to containerised and event-driven services using Docker, Kubernetes, CI/CD pipelines and AWS services.
Write clear, maintainable and well-tested code, and participate constructively in peer reviews and technical discussions.
Collaborate with Product Management, DevOps, Quality Assurance, security specialists and other developers to manage dependencies and support iterative delivery.
Apply secure development, data-handling and responsible AI practices, including appropriate verification of AI-assisted outputs and use of approved tools and accounts.
Share knowledge with colleagues, contribute to team documentation and provide task-specific support to less-experienced team members where appropriate.
Keep technical knowledge current in software engineering, cloud technologies, Generative AI and cybersecurity, and suggest practical improvements within the team’s scope.
What You Will Bring
Degree in Computer Science, Software Engineering or a related discipline, or equivalent practical experience.
Relevant professional software development experience delivering production code within a collaborative engineering environment.
Practical development of web services, microservices or REST APIs using Python or a comparable language.
Involvement across the software delivery lifecycle, including design, implementation, testing, deployment and operational support.
Application of structured problem-solving to varied technical issues within established engineering standards and practices.
Sound Python development skills and the ability to produce readable, maintainable and tested code.
Working knowledge of API development and a framework such as FastAPI, Flask or Django.
Working knowledge of AWS services and cloud-native application concepts.
Working knowledge of Docker, Kubernetes, CI/CD and Unix/Linux development environments.
Ability to use SQL and data stores such as PostgreSQL or Redis; ability to learn related platforms such as Elasticsearch.
Ability to analyse technical information, exercise judgement within defined practices and escalate appropriately when risk or complexity exceeds role scope.
Clear written and verbal communication, with the ability to work productively across engineering and product disciplines.
Ability to use approved AI-assisted development tools responsibly, verify generated outputs and protect confidential, customer and personal data.
Nice to Have:
Contribution to Generative AI, large language model or AI-enabled software solutions.
Work with cloud-native or distributed systems in a cybersecurity, data-intensive or similarly complex domain.
Task-specific coaching, knowledge sharing or support for peers or less-experienced colleagues.
Knowledge of Temporal, event-driven architectures or large-scale data processing.
Understanding of AI agent patterns, retrieval-augmented generation or conversational AI systems.
Knowledge of cybersecurity products or concepts such as XDR, MDR, SIEM or SOAR.
Familiarity with AI-assisted coding tools such as Claude Code, Cursor or Codex.
