Who We Are
We are looking for a hands-on AI Engineer to help improve and scale an internal platform that enables engineering teams to ship faster and safer using AI-powered workflows.

This role is focused on practical AI engineering, not AI research and not pure platform architecture. You will work on agentic workflows, prompt engineering, evaluation pipelines, GitHub-based automation, and developer tooling that helps teams adopt AI agents consistently across repositories.

You will join an existing initiative that already has working foundations in place. The immediate need is to strengthen, stabilise, and mature the current implementation through hands-on engineering, especially in agent development, testing, evaluation, and workflow reliability.

This is an excellent fit for someone who already uses AI coding agents as part of their daily workflow and knows how to turn AI capabilities into reliable engineering tooling.

What You'll Be Doing
- Build and improve AI workflows across repositories
- Design agent workflows for docs, testing, code quality, reviews, and security




- Create effective prompts and multi-step interactions
- Improve reliability and usability of agents
- Use AI coding tools (e.g., Copilot, Cursor) to accelerate delivery
- Design evaluation pipelines for prompts and agents
- Build datasets with edge and adversarial cases
- Add automated regression and behavior checks
- Use code-based and LLM-based evaluators
- Define quality gates before production
- Build reusable templates and onboarding tools
- Develop CLI/scripts for easy adoption
- Maintain workflow catalog and integrations
- Write clear docs and guides
- Enable self-service usage
- Maintain GitHub Actions and CI/CD patterns
- Ensure secure design (least privilege, secrets, OIDC)
- Improve security controls and automation safety
- Mitigate risks (prompt injection, data leaks)
- Keep changes testable and production-safe

What You'll Bring Along
- BSc/MSc in Computer Science or related field

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