Application Developement Senior Analyst

Practical experience delivering application development or configuration within an enterprise environment.

Strong hands-on capability in the core technologies required by the requisition, with the ability to diagnose and resolve technical issues independently.

Understanding of software engineering fundamentals, including modular design, testing, debugging, version control and secure coding.

Experience working in Agile teams and managing work through tools such as Jira and Confluence or equivalent.

Experience with code review, automated testing and CI/CD pipelines.

Ability to communicate technical information clearly to engineering and non-engineering stakeholders.

Sound judgement, attention to detail, ownership and a continuous-learning mindset.

Ability to balance delivery pace with quality, security, maintainability and operational support needs.

Relevant platform certification or equivalent demonstrable experience.

Experience in healthcare, insurance or another regulated industry.

Experience with SAFe or delivery across multiple dependent teams.

Awareness of accessibility, performance engineering and resilient integration design.

Experience using approved AI-assisted development tools to support activities such as code generation, refactoring, unit-test creation, documentation, debugging or code explanation, while applying human review, secure-coding practices and data-handling controls.

Experience using approved generative AI tools in day-to-day work to summarise information, improve written communication, prepare meeting outputs, explore options or streamline repeatable tasks, with appropriate validation of outputs.

An interest in evaluating AI use cases based on measurable value, quality, risk and responsible-use considerations.

Delivery: Completes agreed work predictably, surfaces risks early and follows through to a stable outcome.

Engineering quality: Produces maintainable, tested and secure solutions that meet agreed standards.

Ownership: Handles moderately complex work with limited oversight and takes responsibility for follow-up.

Collaboration: Works constructively across disciplines, contributes to reviews and shares knowledge.

Improvement: Identifies practical ways to reduce rework, strengthen controls and improve team effectiveness.

Responsible AI use: Uses AI as an assistive tool where permitted, validates outputs and never substitutes generated content for engineering accountability.

Bachelor’s degree in Computer Science, Engineering or a related discipline, or equivalent practical experience.

Commitment to ongoing technical learning, including platform, security, cloud, automation and responsible AI capabilities relevant to the role.