About the position
ENVIRONMENT:
JOIN the team of an Online Gaming Group seeking to fill the hands-on technical role of an AI Architect/ Engineer. You will serve as one of the site’s most senior individual technical contributors including to its AI-augmented engineering model. The role exists because the transformation the site has committed to, rebuilding how software is specified, written, tested and released around AI assistance, requires deep hands-on engineering ownership that cannot be delivered from a line management position and cannot be bought in as advisory.
DUTIES:
AI Engineering Harnesses:
- Accountable for the design, build, operation and lifecycle of the internal harnesses that make AI-assisted Engineering safe and repeatable: agent and assistant scaffolding, repository and domain context layers, prompt and workflow libraries, evaluation harnesses, regression and guardrail suites, and the integration of these into the Developer toolchain and CI/CD pipeline.
- Decide on the technical design and implementation of these systems.
AI adoption in delivery:
- Accountable for ensuring AI augmentation actually lands in the delivery teams: reference implementations, integration patterns per stack, Developer enablement, and removal of the technical obstacles that stall adoption.
- Work through Heads of Engineering and Engineering Managers, who retain accountability for their teams’ delivery outcomes.
Domain and technical depth:
- Accountable for holding sufficient depth in business domains — player journey, account and wallet, bonusing and promotions, game integration, payments, responsible gambling controls, regulatory reporting — to judge where AI assistance is safe, where it is not, and what a correct output looks like.
- Own the domain context and knowledge artefacts on which AI-assisted work depends.
Technical standards and architecture practice:
- Accountable for Engineering standards governing AI-assisted development: code provenance and attribution, review obligations for generated code, licensing and IP hygiene, secure coding under assistance, and the definition of done for AI-assisted change.
- Set these standards within the group reference architecture and recommends changes to it where augmentation requires them.
Engineering telemetry and measurement:
- Accountable for the technical instrumentation that makes engineering performance observable, delivery, quality and flow telemetry, and the pipelines and analysis layers that turn it into decision-grade evidence for the Managing Director and group stakeholders.
- Determine the technical implementation; the measurement framework and its interpretation are agreed with the Managing Director and Heads of Engineering.
Technical evaluation and vendor assessment:
- Accountable for the technical evaluation of AI platforms, models, tooling and third-party services proposed for engineering use, including capability benchmarking against workloads, security and data-handling posture, cost model and exit risk.
- Recommend to the Managing Director, who holds selection and contracting authority.
Technical leadership without authority:
- Accountable for raising the technical ceiling of the engineering organisation: mentoring Senior and Lead Engineers, leading design and architecture review, setting the standard for engineering craft, and building the internal advocacy that carries the augmentation model past initial resistance.
- Hold no line authority over any Engineer.
Prototyping and technical risk reduction:
- Accountable for de-risking novel technical initiatives ahead of committed delivery through working prototypes and spikes, and for producing a clear, evidenced recommendation to proceed, adapt or stop.
REQUIREMENTS:
Qualifications –
- Bachelor’s Degree in Computer Science, Software Engineering, Engineering or a related field.
Experience/Skills -
- 10+ Years in Software Engineering, with a sustained record of hands-on delivery at senior or staff-plus level.
- Demonstrated ownership of platform, tooling or Developer-experience systems used across an engineering organisation of comparable scale.
- Practical, shipped experience applying AI or Machine Learning to engineering workflows
- Evidence of technical leadership without line authority across multiple teams.
- Delivery accountability in a regulated, consumer-facing, high-availability environment (advantageous).
Desired Skills:
- AI Architect
- Engineer
- CPT
