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Salary
≈ $14k – $33k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Staff · 8+ years exp

Confirmed on the employer's own hiring board on Oct 5, 2026. First seen by Alion on Sep 24, 2026. Ascendion scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Ascendion is an American technology services company created in 2022 when Collabera's digital engineering business was separated under private equity ownership and rebranded. It builds software, data platforms and applied artificial intelligence for enterprise clients across financial services, healthcare, retail, technology and communications, and it markets itself around engineering delivery accelerated by its own artificial intelligence tooling rather than around headcount. Headquartered in Basking Ridge, New Jersey with its largest delivery base in India, it employs several thousand engineers across North America, Europe and Asia.

Staff AI Quality Engineer -

About the Role

As a Staff AI Quality Engineer -you will lead the technical test strategy and architectural validation for Lenovo’s cross-device agentic AI ecosystem. You will serve as the technical authority on evaluating non-deterministic systems, designing automated quality platforms that operate across personal computing form factors (PCs, tablets, and smartphones). You will drive non-functional quality standards-ensuring that privacy, security, accessibility, internationalization, and device thermals/battery efficiency are safeguarded-while acting as a crucial release partner alongside Product Management and PMO leads.

What Will You Do

  • Test Automation Architecture: Architect scalable, distributed, cross-platform test automation infrastructure capable of executing synchronized, multi-device end-to-end tests across Windows and Android devices without reliance on UI flakiness.
  • Agentic AI Quality Frameworks: Design automated evaluation methodologies to validate multi-step agent reasoning, tool-calling graphs, autonomous error recovery, and transactional rollback mechanisms; establish statistical release gates for non-deterministic model behaviors.
  • Hardware & Runtime Resource Profiling: Formulate automated performance and endurance soak suites to benchmark on-device SLM execution against cloud fallback paths, monitoring thermal throttling, memory leaks, and battery draw across hardware device tiers.
  • Non-Functional Quality Standards: Lead automated verification across non-functional pillars: red-teaming indirect prompt injection vulnerabilities, securing inter-process data barriers, standardizing automated accessibility (screen-reader verbosity, dynamic token streaming), and validating semantic fidelity across international locales.
  • CI/CD Quality Pipelines & Gating: Drive the technical implementation of shift-left gating in continuous integration pipelines, establishing automated failure analytics, regression detection, and flakiness isolation frameworks.
  • Cross-Functional Peer Leadership: Serve as a core technical gatekeeper alongside Product Management and PMO; establish release acceptance criteria, lead data-informed risk assessments during schedule compressions, and influence platform design for enhanced testability.

Basic Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related technical field.
  • 8+ years of progressive software quality engineering, test architecture, and automation experience covering multi-device hardware ecosystems (Windows and Android).
  • 3+ years of experience leading quality strategy and automated evaluation frameworks for LLMs, agentic AI workflows, or conversational platforms.
  • Advanced programming and architecture skills in Python, C++, C#, or Java, with a track record of building scalable test harnesses and mock environments for OS IPC, APIs, and background daemons.
  • Proven experience architecting automated non-functional test frameworks: deep profiling of device performance (NPU/GPU/CPU, battery mA/h, memory), security red-teaming/prompt-injection defense, automated accessibility (WCAG), and i18n semantic evaluation.
  • Deep technical expertise in CI/CD pipeline architecture, test orchestration, and statistical quality gating.

Preferred Qualifications

  • Hands-on expertise implementing and tuning non-deterministic evaluation platforms (e.g., RAGAS, DeepEval, LangSmith, TruLens) in production pipelines.
  • Direct experience testing local NPU runtimes and quantized models (INT4/INT8 vs. FP16) on client silicon (Qualcomm, Intel, AMD).
  • Background designing automated testing for multimodal inputs (synchronized voice injection, screen-capture parsing, synthetic system events).
  • Demonstrated ability to resolve complex release-gating disputes with Product Management and PMO using objective risk metrics and clear mitigation trade-offs.
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