Description
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 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, DevOps optimisation).
- Conduct hands-on testing and technical evaluations to determine each tool’s viability, performance, scalability.
- Compare tools against business/technical requirements including cost-effectiveness; integration complexity; compliance standards.
- Create recommendations on how the client should support or not support various AI tools/models while measuring productivity benefits across different development tasks:
- Perform high-level half-day overview of different tools/models for further investigation
- Complete one-week hands-on experiments with various tools/models across tasks producing recommendations/comparisons against GitHub Copilot default model
- Complete more detailed evaluation on selected AI tooling/platforms enhancing code generation/error detection/testing/DevOps optimisation
Collaboration with Stakeholders
- Engage with development teams; technical leads; product managers identifying challenges/opportunities where AIs can deliver value.
- Present findings/recommendations highlighting strategic benefits from adopting specific AIs.
Integration & Rollout
- Develop strategies/best practices introducing AIs into existing processes ensuring minimal disruption.
- Lead proof-of-concept projects/pilot programmes validating tool effectiveness.
- Support onboarding/training maximising new AIs' benefits through workshops/focus groups etc., producing handbooks/documentation supporting increased adoption.
Performance Monitoring & Optimisation
- Define metrics/KPIs measuring impact from adopted AIs continuously reviewing performance identifying opportunities further optimising usage staying abreast industry trends advances ensuring organisation remains ahead curve.
Governance & Compliance
- Ensure all AIs align organisational policies/security protocols/relevant regulations establishing guidelines ethical/responsible use within developmental processes.