· 6 to 10 years of experience across software engineering, analytics, strategy, finance, or product, including at least 3 years hands-on in AI or building AI-enabled applications. Bachelor’s degree in a quantitative, business, or technical field required; master’s a plus
· Demonstrated experience shipping production AI tools, including LLM applications, retrieval systems, or agentic workflows, from prototype to real users.
· Hands-on experience building with automation/orchestration platforms such as n8n (or a comparable platform) and designing and shipping bespoke applications on AWS. Able to evaluate the trade-off between the two and choose deliberately.
· Solid engineering practice: code in GitHub with reviewed pull requests, tests, and secrets handled properly, and infrastructure defined as code. Working knowledge of CI/CD, environment separation, staged rollout, monitoring, and rollback.
· Strong SQL and solid data modelling instincts, command of Excel, and working knowledge of modern BI tools such as Looker, Power BI, or Tableau. Demonstrated ability to work with messy, real-world data.
· Working command of modern AI technologies, including LLMs, retrieval, agentic workflows, model evaluation, data quality, and the practical limits of AI.
· AI-native approach to development. Comfortable using AI-assisted development tools such as Claude Code as part of your day-to-day workflow to prototype, build, test, and iterate effectively.
· Strong financial and commercial acumen, with the ability to build a credible business case and communicate it clearly to non-technical stakeholders.