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Lumenalta

Agentic Quality Engineering

RemoteNot specified
Published
Role
Unknown
Experience
Senior
Salary not disclosed
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No BS summary

We’re seeking an experienced Agentic Quality Engineer to own the quality and test strategy across a modern, AI-augmented engineering platform. This is a hands-on senior role responsible for defining quality standards, owning technical acceptance criteria, and supervising AI agent-led testing alongside human engineers.

Core skills

AI agent developmentAI agent orchestrationTest automation

Required skills

Playwright/Cypress/JestClaude/CodexGit/JavaScript/TypeScript/Node.js/NPMJira/Confluence/Grafana/Kibana

Optional skills

Anthropic Claude certificationEquivalent credentials in AI agent development or applied AI engineeringPublic evidence of agent work: open-source contributions, published prompt or workflow patterns, talks, or writing on agent-led testingISTQB Advanced Level Test Manager certificationProfessional certifications such as ITIL, BCS, ISACA, or ISC2Experience introducing a new engineering practice across an organization and getting it adopted

Required languages

English excellent

What you'll do

  • Own the agent-led quality model. Define how AI agents are directed, constrained, reviewed, and measured across the testing lifecycle and evolve that model as the capability matures.
  • Orchestrate agents that build and maintain automation. Direct Claude/ Codex, and Codex agents to create and maintain Playwright, Cypress, and Jest suites alongside engineers: generating coverage for new work, repairing suites as the product changes, and expanding depth where risk is highest.
  • Develop the prompting, context, and workflow patterns that make agent-generated tests reliable repo context strategies, guardrails, review gates, and the escalation paths for when an agent should hand back to a human.
  • Set the quality and test strategy for the platform, ensuring quality is engineered in at every stage rather than inspected in at the end.
  • Drive adoption across engineering teams. Onboard squads onto the model, document what works, run enablement, and make the practice self-sustaining without owning headcount.
  • Own technical acceptance criteria in partnership with Product Managers, and lead risk-based functional testing across all stages of development.
  • Plan and manage UAT cycles, environment specifications, execution, and stakeholder reporting.
  • Establish the measurement framework. Define quality KPIs that work for an agent-led model: coverage quality (not just coverage percentage), escaped-defect rates, agent output reliability, and human review load over time.
  • Own service acceptance for complex deliverables.
  • Track where the frontier is moving. Evaluate new agent capabilities, models, and testing technologies, and decide what earns a place in the platform.

What they require

  • Proven leadership experience, including managing others and working in cross-team and cross-organizational environments.
  • Hands-on AI agent development and orchestration. Practical, sustained experience directing Claude, Claude Code, Codex, or equivalent coding agents on real engineering work, not experimentation. You should be able to talk concretely about context management, prompt and workflow design, where agents fail, and how you designed around it.
  • Experience supervising agents in a testing context using them for coverage generation, defect detection, or suite maintenance, and applying real judgment to their output.
  • Expert test automation proficiency with Playwright, Cypress, and Jest (or close equivalents). You need to be able to read, judge, and fix what an agent produces.
  • 7+ years in QA or test engineering, including setting strategy across multiple teams.
  • Expert-level functional testing and UAT management.
  • Ability to define measurement frameworks and quality KPIs from scratch, in a model where the traditional metrics do not fully apply.
  • Solid engineering foundations: microservices and API architecture, Git, JavaScript/TypeScript, Node/NPM.
  • Expert familiarity with Jira, Confluence, Grafana, and Kibana.
  • Strong agile background and excellent English communication skills.

Partners with global enterprises to design and scale data platforms powering products used by millions, involving large-scale data systems, complex pipelines, and high-impact business use cases across multiple industries.

FintechMid-size
Salary not disclosed