Senior QA Engineer, AI Agents & Agentic Workflows

Job Description

QAD is seeking a Sr QA Engineer to own the continuous validation and quality of Champion Assist, a multi-

agent AI product with ~20 evolving agents. You will test the agents themselves: their reasoning, tool use,

orchestration and handoffs, and the quality of their responses. This goes beyond UI and API checks.

You will design evaluation frameworks and regression suites that catch failures unique to non-deterministic, LLM-

driven systems.

Responsibilities:

• Design, run and maintain end-to-end business scenarios that exercise multi-step agentic workflows,

including agent routing, tool/function calls, and multi-turn conversations.

• Evaluate agent outputs for correctness, relevance, groundedness, consistency, tone and

completeness, using both human review and automated methods.

• Build and maintain eval datasets (golden sets, edge cases, adversarial prompts) and automated

regression suites that run as agents, prompts, models and tools change.

• Identify cross-agent, orchestration and integration issues: wrong agent selection, broken handoffs,

tool-call failures, context loss, looping or runaway behavior.

• Test for hallucination, prompt injection, jailbreaks, data leakage and unsafe or out-of-scope responses.

• Detect regressions caused by model upgrades, prompt changes or retrieval/knowledge changes, and

quantify them with metrics.

• Triage and root-cause issues with Engineering and Product, separating prompt, model, retrieval, tool

and orchestration causes.

• Re-test fixes, validate the end-user experience, and keep evals current as the product evolves.

• Document test strategy, eval results and quality trends clearly for global stakeholders.

Qualifications

• Bachelor's degree in software engineering, computer science or a related field.

• 3-5 years of QA experience, with at least 1-2 years testing LLM-based applications, AI agents or

agentic workflows.

• Hands-on experience evaluating non-deterministic outputs: defining pass/fail criteria, rubrics, and

acceptance thresholds for AI responses.

• Experience building or maintaining AI eval or regression suites (e.g., LLM-as-judge, golden datasets,

scoring rubrics).

• Understanding of agentic concepts: tool/function calling, multi-agent orchestration, planning,

memory/context, RAG.

• Experience with test automation tools (Selenium, Playwright, TestComplete or similar) and API testing.

Additional Information

• Your health and well being are important to us at QAD. We provide programs that help you strike a healthy work-life balance.
• Opportunity to join a growing business, launching into its next phase of expansion and transformation.
• Collaborative culture of smart and hard-working people who support one another to get the job done.
• An atmosphere of growth and opportunity, where idea-sharing is always prioritized over level or hierarchy.
• Compensation packages based on experience and desired skill set

About QAD:

QAD | Redzone is redefining manufacturing and supply chains through its intelligent, adaptive platform that connects people, processes, and data into a single System of Action. With three core pillars — Redzone (frontline empowerment), Adaptive Applications (the intelligent backbone), and Champion AI (Agentic AI for manufacturing) — QAD | Redzone helps manufacturers operate with Champion Pace , achieving measurable productivity, resilience, and growth in just 90 days.

QAD is committed to ensuring that every employee feels they work in an environment that values their contributions, respects their unique perspectives and provides opportunities for growth regardless of background. QAD’s DEI program is driving higher levels of diversity, equity and inclusion so that employees can bring their whole self to work.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.