Full Description

Roles & Responsibilities

• Quality Leadership & Culture
• Own accountability for end-to-end quality outcomes across 2 global teams (~25 engineers).
• Champion a shift-left quality culture, embedding testing in design, code reviews, and CI/CD.
• Partner closely with AI Engineers to embed quality into day-to-day development.
• Partner with the Platform QE Engineering team to ensure AI apps meet platform-level quality and scalability standards.
• Partner with Technical Product Managers (TPMs) and Technical Product Owners (TPOs) to ensure quality requirements are captured and addressed.
• Define and track team-level quality OKRs and KPIs.
• Functional Quality
• Architect and implement automation frameworks (UI, backend, API, mobile).

Build evaluation frameworks for

• LLM/SLM non-deterministic responses.
• Prompt and agent orchestration reliability.
• RAG + Vector DB use cases (retrieval relevance, semantic correctness, failure fallback).
• Hallucination detection, bias, fairness, and safety.
• Integrate AI evaluation into CI/CD pipelines with dashboards and gating criteria.
• Operational Quality (Enablement Role)
• Define strategies for load, performance, and reliability testing.
• Establish frameworks and test patterns for evaluating latency, concurrency, token efficiency, and response unpredictability.
• Ensure teams conduct and observe LnP (Load & Performance) tests and capture quality signals.
• Act as an enabler and coach, ensuring practices are scalable and team owned.
• Security & Compliance Quality
• Collaborate with the Ascend Penetration Testing team to ensure coverage of security risks (prompt injection, adversarial attacks, access control, and data leakage prevention).
• Establish additional security validation practices (input/output sanitization for healthcare/education data).
• Ensure compliance with Ascend ITGC, PCI, PII, CCPA where applicable.

Required Skills & Qualifications

• · This role requires deep awareness of quality challenges unique to LLM- and SLM-powered Agentic AI applications, especially in healthcare and education, where correctness, reliability, and compliance are essential.
• 7+ years in Quality Engineering/Automation, with 3 years in QA leadership roles.
• Proven experience transforming teams from manual QA to automation-first.
• Awareness of LLM/SLM quality challenges (latency unpredictability, token inefficiency, hallucinations, SME UAT cycles).