You'll work within a forward deployed engineering team or a delivery pod aligned to one of our service lines, alongside a product manager and under the technical direction of a Lead Engineer.
The work spans the full stack of what engineering needs to do around a GenAI platform: solving problems natively, backend plumbing, API integrations, MCP server builds, and data connections.
Working in our GenAI platform doesn't always mean writing code. Often it means applying engineering judgement to solve problems natively, designing the right architecture, the right integration, the right data flow, directly within the platform itself.
At Senior Engineer level, you'll own your delivery end-to-end.
You translate business need into solutions and technical design, and work individually or as part of the team to solve those in the best way at pace.
At Engineer level, you'll deliver well-crafted, production-grade solutions within the team's technical direction. You own the quality of your output, raise blockers early, and build depth and judgement as your experience grows.
You're fluent across AI-native engineering from building natively in the platform, using AI tooling to accelerate your own craft, and taking coalface experiments through to production-grade operationalised solutions.

At Senior Engineer level you have a track record of owning delivery end-to-end in a team-based model.
You've shipped production software and can speak to the decisions you made.
You have real depth in backend and integration engineering using Python or C# .Net, and genuine judgement about when to solve natively in the platform and when bespoke engineering is the right call.
At Engineer level you have demonstrable experience building and shipping working software.
Solid foundations in at least one backend language, understanding of APIs and version control, and the instinct to take ownership of your work rather than stop at the task boundary.
Across both levels familiarity with Azure and Microsoft 365 is an advantage.
Hands-on experience with LLM integration patterns, MCP tooling, and AI-enabled or agentic development environments is genuinely valued.
AI and LLM experience
you're comfortable using GenAI tools such as Copilot, Claude or ChatGPT.

Software Engineer

Key skills