Description
As a senior member of our software engineering team, you'll be expected to provide technical direction and mentorship to less experienced colleagues. You will be a hands-on practitioner responsible for deploying, operating and maintaining software services across a variety of platforms, from standalone systems to large Kubernetes clusters on cloud platforms, and everything in between.
Responsibilities
•Provide technical direction and mentorship to less experienced colleagues
•Deploy, operate and maintain software services across a variety of platforms, from standalone systems to large Kubernetes clusters on cloud platforms, and everything in between
•Deploy and operate software services on established platforms, building, maintaining, and continuously improving Kubernetes-based deployments
•Develop and optimise CI/CD pipelines and release automation to ensure seamless delivery
•Apply Site Reliability Engineering principles to production services, and monitor service health, performance, availability, and reliability to maintain high standards of stability
•Troubleshoot deployment and operational issues, and work to improve observability, incident response, and general operational processes
•Make appropriate use of AI-assisted tools to improve delivery efficiency
•Collaborate closely with development, platform, and infrastructure teams, seeking out opportunities to reduce manual effort and increase the speed of deployment
Requirements
•Self-motivated, with high standards and a commitment to excellence
•Experience of using AI within engineering processes, reviewing the output of AI, guiding AI to produce software and deployments that meet corporate standards
•Experience integrating AI capabilities into production systems, including familiarity with emerging standards such as the Model Context Protocol (MCP)
•A relevant degree or equivalent experience in industry
•A passion for writing code, improving processes, and communicating with technical and non-technical colleagues alike
•Constantly looking to improve yourself and learn new things, and thriving in a fast-paced, dynamic environment
Conditions & Benefits
•Access to a broad mix of learning opportunities, including in-house and online training, technical deep dives and development pathways shaped around your interests and the needs of the organisation
•Support to strengthen capability across modern AI techniques, Cloud technologies and wider analytical or engineering practices
•Support with the Government Digital and Data Profession Capability Framework
•Opportunities to work with external professional bodies and training providers offering routes to specialist accreditation, advanced AI training and broader professional recognition
•Mentoring, peer support and a collaborative community that shares knowledge openly
•Opportunities to rotate across different teams, explore emerging technologies and contribute to shaping how the organisation evolves its AI and data science capability
•Space to experiment, increase expertise and play an active role in strengthening the AI practice across the organisation
•25 days annual leave, automatically rising to 30 days after 5 years' service
•An additional 10.5 days of public and privilege holidays
•Opportunities to be recognised through the employee performance scheme
•Interest-free season ticket loan (travel and parking)
•Pension scheme with employer contributions of at least 28.97%
•Cycle to work scheme
•A subsidised gym and an on-site restaurant/coffee shop
•Paid parental and adoption leave
