Senior AI Engineer

Role Description: Senior Engineer – AI Tooling Assessment

Role Overview

We are seeking a highly experienced Senior Engineer to lead the assessment and adoption of AI tooling within our development teams. This role is integral to ensuring our organisation remains a leader in using AI to improve software delivery processes. As the Senior Engineer, you will evaluate emerging AI tools for code generation, guide their integration into our workflows, and ensure they provide measurable value to our teams.

The Person:

This is a pivotal role that will shape the future of our development practices, ensuring our teams are equipped with the best AI tools to deliver exceptional results.

Extensive fullstack experience in a senior engineering role, with a focus on innovation and emerging technologies.

Highly experienced in the use of GitHub Copilot and other tools/models that use AI for code generation

Strong understanding of AI and machine learning concepts, including their practical application in software development.

Solid background in software engineering, CI/CD pipelines, and modern programming practices.

Start-up mindset, highly proactive and adaptable, and passionate about AI as an enabler for engineering; thrives in fast-paced environments.

Exceptional communication and leadership skills, with the ability to influence and collaborate with stakeholders at all levels.

Able to articulate to both technical and business stakeholders the pros and cons of different tools and approaches

Strategic thinker with a forward-looking approach to technology adoption.

Able to commute up to 3 days a week into Old Street office and (optionally) Waterside, if and when required. Before then, there is an expectation of 2 days per week in the office.

Key Responsibilities

Assessment of AI Tools

Research and evaluate AI tools and platforms that can enhance software development practices (e.g. code generation, error detection, testing, and DevOps optimisation).

Conduct hands-on testing and technical evaluations to determine each tool’s viability, performance, and scalability.

Compare tools against business and technical requirements, including cost-effectiveness, integration complexity, and compliance standards.

Create recommendations of how the client should support or not support a range of AI tools / models and measure the benefit on productivity for a range of development tasks:

Perform high-level ½ day overview of different tools / models to see which warrant further investigation

Complete 1-week hands-on experiments with different tools and models for a range of tasks and produce recommendations / comparisons with the GitHub Copilot default model

Complete more in-depth evaluation of any selected AI tools and platforms to enhance code generation, error detection, testing, and DevOps optimisation

Collaboration with Stakeholders

Engage with development teams, technical leads, and product managers to identify challenges and opportunities where AI tools can deliver value.

Present findings and recommendations to senior leadership, highlighting the strategic benefits of adopting specific AI tools.

Integration and Rollout

Develop strategies and best practices for introducing AI tools into existing processes, ensuring minimal disruption.

Lead proof-of-concept projects and pilot programmes to validate tool effectiveness.

Support teams with onboarding and training to maximise the benefits of new AI technologies.

Assist in rolling out and increasing adoption of AI software development tools, through workshops, focus groups, etc

Produce handbooks and documentation to support the increased adoption of AI Code Generation tools

Performance Monitoring and Optimisation

Define metrics and KPIs to measure the impact of adopted AI tools.

Continuously review the performance of tools in use, identifying opportunities for further optimisation.

Stay abreast of industry trends and advances in AI tooling to ensure the organisation remains ahead of the curve.

Governance and Compliance

Ensure that all AI tools align with organisational policies, security protocols, and relevant regulations.

Establish guidelines for ethical and responsible use of AI in development processes.