Your mission

Most of what makes an AI solution survive contact with a large enterprise is not the AI. It is the engineering discipline around it, and that discipline is what you bring. You do not need to arrive as an AI expert - you arrive as someone who knows how professional software gets built, shipped, and kept alive, and you grow into the agentic side alongside a team that is already deep in it. In our Engineering team you set the bar for what production-ready means here.

Your tasks will include:

Designing the technical approach for a system slice, from build and test through deployment and operation, including the documentation and artefacts a third party needs to run it without us
Shaping how we develop: issue workflows, branching and review standards, CI/CD pipelines, automated testing, security checks, and release management
Building the classical software around the AI core - services and APIs, data pipelines, infrastructure as code, mostly in Python on Azure
Making solutions operable in enterprise IT landscapes: observability, failure behaviour, security posture, and cost transparency
Providing specialist guidance that shapes technical decisions across workstreams, and raising the engineering bar through design and code reviews
Making technical trade-offs legible to senior client stakeholders - what a given architecture or operating model costs and enables

Your profile

8+ years building software that went into production and stayed there, ideally shaped by a product organisation with real release discipline
Deep working knowledge of the professional software development lifecycle: issue tracking and workflows (e.g. Jira), code review and development standards, CI/CD, automated testing, security scanning, versioning and releases
Strong Python, confidence on Azure, and hands-on experience with containers and infrastructure as code
Experience handing a system over to a separate operating team, or having operated one yourself long enough to know what that handover really demands
Some exposure to GenAI or agentic systems and genuine curiosity to go deeper; deep AI expertise is explicitly not a prerequisite
Composure in fast-moving, ambiguous environments, and the ability to explain technical trade-offs clearly to senior stakeholders in English

Responsibilities

Your mission

Your tasks will include:

Designing the technical approach for a system slice, from build and test through deployment and operation, including the documentation and artefacts a third party needs to run it without us
Shaping how we develop: issue workflows, branching and review standards, CI/CD pipelines, automated testing, security checks, and release management
Building the classical software around the AI core - services and APIs, data pipelines, infrastructure as code, mostly in Python on Azure
Making solutions operable in enterprise IT landscapes: observability, failure behaviour, security posture, and cost transparency
Providing specialist guidance that shapes technical decisions across workstreams, and raising the engineering bar through design and code reviews
Making technical trade-offs legible to senior client stakeholders - what a given architecture or operating model costs and enables

Your profile

8+ years building software that went into production and stayed there, ideally shaped by a product organisation with real release discipline
Deep working knowledge of the professional software development lifecycle: issue tracking and workflows (e.g. Jira), code review and development standards, CI/CD, automated testing, security scanning, versioning and releases
Strong Python, confidence on Azure, and hands-on experience with containers and infrastructure as code
Experience handing a system over to a separate operating team, or having operated one yourself long enough to know what that handover really demands
Some exposure to GenAI or agentic systems and genuine curiosity to go deeper; deep AI expertise is explicitly not a prerequisite
Composure in fast-moving, ambiguous environments, and the ability to explain technical trade-offs clearly to senior stakeholders in English