Requirements

Proven experience designing, developing and deploying software tools, integrations or automation solutions actively used by others.
Hands-on software development experience using Python, JavaScript or similar languages with understanding of APIs, data integration, and automation pipelines.
Experience owning technical solutions from problem identification through implementation, deployment and ongoing support.
Practical experience using AI-assisted development tools or AI technologies to improve software development or automate workflows.
Ability to work independently, identifying improvement opportunities and translating ambiguous business challenges into technical solutions.
Experience collaborating with stakeholders, gathering requirements, and communicating technical concepts to both technical and non-technical audiences.
Strong problem-solving skills, including troubleshooting, data quality assessment, and ensuring reliability of deployed solutions.
Proactive, collaborative mindset with a record of delivering meaningful improvements through technical contributions.

Nice to Haves

Experience developing or deploying AI agents, LLM-powered applications, or agentic automation workflows.
Familiarity with Jira, Confluence or similar platforms, including their APIs and integration capabilities.
Experience with cloud platforms, deployment pipelines, CI/CD, or infrastructure supporting automated workflows.
Developing dashboards, reporting tools or data visualizations supporting operational or engineering decision-making.
Understanding of software engineering delivery processes including requirements, milestones, dependencies, and resource planning.
Experience building internal developer tools, productivity solutions, or automation platforms used across multiple teams.
Familiarity with developer ecosystems, AI platforms, or open-source software.

Designing and building automation solutions to simplify complex workflows and improve efficiency across engineering and business teams.
Owning solutions end-to-end: engaging directly with stakeholders to define requirements, develop and deploy reliable tools.
Building integrations and automated pipelines across platforms such as Jira, Confluence, and internal tools to enhance information accessibility and accuracy.
Applying AI to real-world challenges by implementing AI-assisted workflows and agents to automate routine tasks and improve decision-making.
Developing dashboards, automated reporting, and data quality checks that surface progress, dependencies, risks, and focus areas.
Collaborating with business unit leaders, engineering teams, and stakeholders to understand needs, challenge processes, and introduce improvements.
Ensuring solution reliability through testing, deployment, monitoring, and continuous improvement as business needs evolve.

Opportunity to combine software engineering, AI, automation, and business collaboration making a visible impact.
Autonomy to take ownership of challenges, shape solutions, and influence team operations across a global technology organization.
Freedom to explore new ideas and emerging technologies alongside talented engineers and business leaders.
Exposure to senior leaders and stakeholders with opportunities to gain recognition for your work.
Supportive hybrid working environment balancing high performance and personal wellbeing, with flexible team-based patterns.
Commitment to equal opportunities in a diverse and respectful workplace.
Potential support for skilled worker sponsorship costs related to the employer.