Quality Assurance Lead

We are seeking an experienced QA Lead to own quality across the NeuBird AI platform. This is a highly hands‑on leadership role that combines technical testing expertise, team leadership, process development, and quality strategy. You will define and execute our overall testing strategy, establish quality standards, build scalable automation frameworks, and lead a distributed QA team. You'll partner closely with engineering, product, and leadership teams to ensure we maintain exceptional product quality while continuing to move quickly and innovate. This role reports to Engineering Leadership and will play a critical role in shaping the culture, processes, and tooling that define quality at NeuBird AI. Responsibilities Quality Strategy & Execution Own end‑to‑end quality across NeuBird AI products, including Hawkeye, Falcon, and supporting platform services. Define testing strategies covering UI, API, integration, regression, infrastructure, and AI‑specific testing. Establish release quality gates and provide go/no‑go recommendations for production releases. Build and maintain test coverage maps, quality metrics, dashboards, and reporting. Drive root‑cause analysis of production issues and identify opportunities for continuous quality improvement. Automation & Test Infrastructure Design and implement scalable automation frameworks for UI, API, and end‑to‑end testing. Build and maintain regression suites and supporting test infrastructure. Integrate automated testing into CI/CD pipelines to support fast and reliable releases. Continuously improve automation coverage, testing efficiency, and overall engineering productivity. AI & Platform Validation Develop testing methodologies for AI‑powered systems, including evaluation of non‑deterministic outputs, RCA accuracy, and agent reliability. Build and maintain realistic infrastructure test scenarios involving Kubernetes environments, database failures, backup and recovery workflows, service degradation, failover events, and observability pipelines. Validate system behavior across logs, metrics, traces, alerts, and incident workflows. Ensure customer‑facing scenarios are thoroughly covered through testing and validation. Lead and mentor a distributed QA team across multiple time zones. Coordinate testing activities, review automation contributions, and coach team members. Establish lightweight and effective QA processes appropriate for a fast‑moving startup environment. Partner with engineering teams during planning and development cycles to identify quality risks early. Act as the voice of the customer when balancing product velocity and reliability. Requirements 5–8+ years of QA experience, including leadership or team management responsibilities. Strong experience testing B2B SaaS, cloud, infrastructure, observability, or DevOps platforms. Hands‑on expertise with modern test automation frameworks such as Playwright, Selenium, pytest, or TestNG. Experience testing distributed systems, APIs, microservices, and cloud‑native applications. Strong understanding of AWS, Kubernetes, containers, CI/CD pipelines, and monitoring and observability platforms. Excellent debugging, troubleshooting, and analytical skills. Strong written and verbal communication skills. Preferred Qualifications Experience testing AI‑powered products, LLM‑based applications, or agentic AI systems. Familiarity with AI evaluation methodologies, model validation, output scoring, or judge‑based evaluation frameworks. Understanding of production incident management, root cause analysis, and Site Reliability Engineering (SRE) practices. Experience building QA processes and quality programs within startup environments. You Will Thrive If You Lead by example and enjoy remaining hands‑on with testing and automation. Can evaluate whether a system output is truly correct, not just whether a test passed. Balance quality, speed, and pragmatism effectively. Build processes that improve quality without introducing unnecessary overhead. Enjoy solving complex technical problems and collaborating closely with engineering teams. Are excited about shaping quality practices for next‑generation AI products. #J-18808-Ljbffr