Lead AI Engineer - Quality Engineering

Responsibilities
We are looking for a Lead AI Engineer to design, build, and operate intelligent agents that automate software testing end-to-end.
This is an AI engineering role applied to quality engineering - not a traditional test automation role with AI added on top. You will own agentic workflows across test-case generation, automation-script creation, execution, validation, failure analysis, self-healing, and continuous test maintenance. The role integrates AI agents with application knowledge, automation tools, APIs, databases, and CI/CD pipelines to enable reliable end-to-end testing and sets the technical direction for how agentic quality engineering is delivered across teams.
You will lead the technical direction of this capability and mentor a team of engineers (team size: TBC) as the practice scales.
Key Responsibilities
Build agentic systems
Design and develop autonomous and multi-agent workflows for test automation.
Build AI agents using LLMs, prompt engineering, RAG, tool calling, and MCP-based integrations.
Develop agents for test generation, code creation, validation, debugging, failure triage, and self-healing.
Maintain application knowledge bases (embeddings, retrieval, context strategy) and continuously improve agent decision-making.
Make them reliable
Define agent instructions, guardrails, validation checkpoints, and human-in-the-loop review processes.
Establish evaluation practice: golden datasets, regression evals, LLM-as-judge where appropriate, and clear accuracy/reliability metrics.
Instrument agents with tracing and observability; monitor and improve accuracy, reliability, latency, token cost, and maintainability in production.
Integrate and ship
Integrate agents with UI, API, database, and end-to-end testing workflows.
Integrate agentic solutions with GitHub, Jenkins, APIs, databases, and other engineering tools.
Lead
Set technical standards and best practices for agentic development and AI-assisted testing.
Mentor engineers, run design reviews, and raise the team's level of AI engineering maturity.