Full Stack AI Engineer

Who This Role Is For

We are looking for a hands-on

Software Engineer

with strong

AI engineering capabilities

who can build production AI systems and work directly with the teams using them.

This role spans full-stack development, LLM applications, evaluation, observability, deployment, and customer-facing technical delivery.

Accessibility experience is not required, but you should be willing to develop expertise in digital accessibility and WCAG standards.

What You Will Do

Design, develop, and maintain high-quality features and services for product teams, ensuring accessibility and performance.

Develop full-stack features across frontend, backend, APIs, data, and AI systems.

Design and build production-grade applied AI-powered applications and developer tools.

Utilise CI/CD pipelines to ensure seamless, reliable, and high-quality deployments.

Develop and maintain technical documentation, including API specs, troubleshooting guides, and system architecture diagrams.

Translate customer feedback and production issues into reusable product improvements.

Work alongside Product Management to provide L1/L2 support to customers.

Work directly with teams on discovery, demos, Proof-of-Concepts, architecture discussions, onboarding, integrations, and troubleshooting.

Gain knowledge debugging and remediating WCAG accessibility issues on production websites.

What We're Looking For

Proven experience in designing and building scalable, reliable, and maintainable software systems.

Strong proficiency in modern software development (e.g., React.js, TypeScript, Node.js) and a deep understanding of browser architecture.

Build LLM workflows using:RAGTool callingStructured outputsAgentsHuman-in-the-loop patterns

Build evaluation pipelines using:Golden datasetsRegression testsDeterministic evaluatorsLLM-as-a-judge

Implement observability, monitoring, guardrails, fallbacks, and validation for reliable AI systems.

Balance model quality, latency, reliability, maintainability, and cost.

Maintain automated tests, CI/CD pipelines, and technical documentation.

Hands-on experience with quality engineering practices, including:Automated testing (unit, integration, E2E)Test automation frameworks

Solid grasp of CI/CD, infrastructure concepts, and agile engineering practices.

Strong troubleshooting and debugging skills, with an ability to analyze complex system behaviors and logs.

Excellent communication skills to explain technical trade-offs and quality standards to diverse stakeholders.

Nice to Haves

Docker, Infrastructure as Code, and Bash scripting knowledge.

Passion for building inclusive technology and a willingness to apply or develop expertise in WCAG 2.2 standards and assistive technologies.

Willingness to learn digital accessibility, including:Digital accessibility regulationsWeb Content Accessibility Guidelines (WCAG) 2.2 Level A and AA requirementsScreen readers such as VoiceOver, NVDA, and TalkBack

Experience writing code that meets accessibility standards such as the Web Content Accessibility Guidelines (WCAG).

Candidates with more than 3 years of relevant experience in software engineering may be considered for senior positions.