As a Software Engineer you will be a key contributor within a cross-functional engineering squad, responsible for building secure, scalable, and high-quality software with an increasing emphasis on AI-driven capabilities and intelligent agent development. You will work closely with Senior Engineers, the Engineering Team Leader, and the Architect to implement modern engineering practices, integrate AI models and agent patterns, and contribute to the evolution of our cloud-native services. You will already have strong software development experience and have a desire to grow deeper into engineering, while maintaining strong software craftsmanship and delivery discipline.
As we move toward an AI-first engineering strategy with multiple autonomous squads, the Software Engineer plays a vital role in delivering reliable, secure, and modern software while developing skills that contribute to our ecosystem. You will help implement AI capabilities, support cloud-native services, and strengthen the squad’s engineering excellence as we scale.
Key Responsibilities
Software Development & Delivery:
- Design, build, test, and maintain high-quality software components and services across backend, frontend, or full-stack environments.
- Utilise AI Accelerated development tools across the SSDLC to accelerate delivery and product quality.
- Write clean, maintainable, secure code following engineering standards and SSDLC best practices.
- Participate actively in backlog refinement, sprint planning, story estimation, and team ceremonies.
AI Integration & Emerging Skills Development:
- Champion AI Enablement initiatives by embedding AI thinking into product design and delivery, enabling teams to leverage AI, and emerging technologies to enhance functionality, automation, and user experience.
- Use vector databases, embeddings, and retrieval pipelines with support from senior engineers.
- Contribute to building robust tests and evaluation checks for AI behaviours and outputs.
- Follow architectural guidance to ensure AI features remain safe, secure, and reliable.
Quality Engineering & Secure Development:
- Create automated tests, including unit, integration, and functional tests.
- Apply secure-by-design principles in all coding activities, participating in threat modelling where appropriate.
- Contribute to code reviews and continuously improve code quality within the squad.
- Maintain documentation for services, features, and reusable components.
Cloud-Native Engineering & DevOps Practices:
- Deploy and maintain services using CI/CD pipelines.
- Instrument code for observability, logging, and performance insights.
- Participate in incident resolution and root-cause analysis for issues within the squad’s domain.
- Follow best practices for cloud development, working across AWS or Azure environments.
Collaboration & Team Contribution:
- Work closely with Senior Engineers and the Engineering Team Leader to confirm technical designs and implementation details.
- Collaborate with Product Owners to understand requirements and propose feasible approaches.
- Communicate progress, blockers, and technical details clearly within the squad.
- Participate in continuous improvement initiatives and share learnings with peers.
Skills & Experience
- Experience as a software engineer within modern cloud-native environments.
- Strong development skills in at least one of the following languages/frameworks: C# .NET, Node, React, Python, React
- Understanding of AI First development and deployment processes.
- Experience building REST APIs, microservices, or modern frontend applications.
- Good grasp of secure coding, testing strategies, and CI/CD pipelines.
- Work collaboratively in an Agile squad with a focus on quality, delivery, self-reflection and improvement.
- Strong problem-solving skills and willingness to learn and adopt emerging AI and agent technologies.
- Hands-on experience with vector databases, embeddings, or prompt engineering.
- Understanding of AI fundamentals and experience using LLM APIs or AI-enhanced features and Agents.
- Experience with cloud services such as AWS, Azure, or serverless platforms.
- Interest in distributed systems, event-driven architectures, or DDD concepts.
- Familiarity with observability tooling and debugging complex systems.