Quality Engineering Lead

About LimeIQLimeIQ is a specialized FinTech/InsurTech platform serving the global specialty insurance and reinsurance market, with deep alignment to the Lloyd’s of London ecosystem. We transform how managing agents, brokers, underwriters, and delegated authorities ingest, validate, reconcile, and analyze bordereaux and claims data.At the core of our platform is LincolnSmart™, our proprietary ingestion and transformation engine that processes large-scale claims and premium bordereaux (BDX) files with precision and consistency. LimeIQ eliminates manual reconciliation, enforces validation rules aligned to market standards, and standardizes fragmented data into structured, auditable datasets.Through our four pillars—Ingestion, Validation, Aggregation, and Intelligence—we enable:✔ Real-time visibility into Lloyd’s portfolio and claims data✔ Automated validation, FCP reconciliation, and exception management✔ Accurate reserve, incurred, and catastrophe reporting✔ Reliable KPI and performance analytics for underwriting and finance teamsOur mission is to build the leading insurance data intelligence platform for the specialty market by enforcing data integrity, operational discipline, and technical excellence.Position SummaryWe are seeking a Quality Engineering Lead to own quality across LimeIQ’s entire platform, covering both software verification and data validation. This is a player-coach role that sets the quality strategy for LincolnSmart™ and the LimeIQ web applications, API and microservices, and for the claims and premium bordereaux (BDX) data flowing through them.You will define how we test, what “done” means, and how quality is measured, while remaining hands-on in validating complex transformation logic, reconciliation outputs, and Lloyd’s market requirements. You will also lead the adoption of modern, AI-enabled QA practices to increase coverage, speed, and defect detection without compromising auditability.This is a leadership role suited to professionals who understand that in insurance, software quality and data quality are inseparable: a defect in code becomes an error in reserves, reporting, or compliance.You will work closely with product managers, software engineers, data engineers, and DevOps, and will guide and mentor QA analysts, including our Data Quality Analysts.This position is based in LimeIQ’s Plano, TX Headquarters.Key ResponsibilitiesDefine and own the end-to-end QA strategy covering software, API, integration, performance, security-minded, and data validation testingLead, mentor, and prioritize the work of QA and Data Quality Analysts, setting standards, coaching on technique, and reviewing test deliverablesEstablish release quality gates, entry/exit criteria, and go/no-go recommendations for production deployments across all environmentsOversee validation of claims and premium BDX ingestion, transformation, reconciliation, and aggregation against Lloyd’s reporting standards and client specificationsVerify financial calculations including reserves, paid, incurred, outstanding, and adjustments, and ensure reconciliation of source files to transformed outputsArchitect and maintain automated test frameworks for UI, API, and data pipelines, integrated into CI/CD (GitHub Actions) as automated quality gatesApply AI to QA: generate and maintain test cases from requirements and user stories, use AI-assisted and self-healing test automation, and apply AI/ML-based anomaly detection to data validationEvaluate and validate AI-enabled product features, including accuracy, consistency, bias, and regression of LLM or ML outputs, using defined evaluation datasets and acceptance criteriaDefine the governance for responsible AI use in QA, including human review, data privacy, prompt and output traceability, and audit-ready evidenceOwn defect management and triage with engineering: severity and priority standards, root-cause analysis, and trend reportingBuild and report quality metrics (coverage, defect escape rate, automation rate, data accuracy and reconciliation pass rates) to the Director of Engineering and leadershipDrive shift-left practices: review requirements and designs, define acceptance criteria, and embed quality in Agile ceremoniesPlan and coordinate regression, integration, performance, and UAT cycles with product, client, and delivery teamsMaintain test data management, environment readiness, and audit-ready test documentation and control frameworksKey Skills & ExpertiseQuality Leadership & StrategyProven experience leading QA teams or acting as the senior QA owner across software and data validationAbility to build test strategy, quality gates, and metrics programs from the ground upStrong risk-based test planning and prioritization under delivery pressureModern QA & AI SkillsHands-on use of AI coding and testing assistants (e.g., Claude, GitHub Copilot) for test design, test data generation, code review, and defect analysisExperience with AI-assisted or agentic test automation, including self-healing locators and automated test maintenanceSkilled prompt engineering, and the ability to validate and govern AI-generated tests and outputs rather than trust them blindlyExperience testing AI/LLM-enabled features: evaluation datasets, output scoring, regression of model behavior, and hallucination and bias checksFamiliarity with ML-based anomaly detection and data profiling for data quality monitoringTest Automation & Technical SkillsStrong web application and API test automation experience (e.g., Playwright, Cypress, Selenium, Postman)Strong SQL skills (SQL Server) for data interrogation and reconciliationWorking knowledge of Python, PowerShell, or similar scripting languagesExperience integrating automated tests into CI/CD pipelines (GitHub Actions) and working with Azure-based environmentsExperience with performance and load testing tools (e.g., k6, JMeter) preferredExperience with JIRA and ConfluenceInsurance & Data DomainExperience with Lloyd’s of London data, managing agents, or delegated authority reporting preferredUnderstanding of claims, risk, or premium bordereaux structures and FCP/market reporting workflowsProven experience validating financial and actuarial-related data and reconciling large datasetsProfessional SkillsMeticulous documentation and audit-ready testing practicesAbility to challenge assumptions and question questionable data or resultsStrong communication with technical and business stakeholders, including influencing release decisionsCoaching mindset with the ability to develop and hold a team to a high standardQualificationsBachelor’s degree in Computer Science, Information Systems, Finance, or related field7+ years of experience in QA, test automation, or data validation, including 2+ years leading or mentoring a QA teamDemonstrated experience applying AI tools to QA workflows in a production environmentAdvanced SQL proficiency and experience with test automation frameworksExperience working in Agile/Scrum environmentsExperience with insurance, reinsurance, or Lloyd’s data environments preferredExposure to regulated financial or insurance systems strongly preferredWhat We OfferA fast-paced environment with high visibility and impactA collaborative team with a shared focus on excellence and accountabilityOpportunity to build and lead the quality function at a growing technology firm, with the mandate to shape our AI-enabled QA practiceA culture rooted in respect, transparency, and ownership