Quality Engineering Lead

About LimeIQ

LimeIQ 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 teams

Our mission is to build the leading insurance data intelligence platform for the specialty market by enforcing data integrity, operational discipline, and technical excellence.

Position Summary

We 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 Responsibilities

• Define and own the end-to-end QA strategy covering software, API, integration, performance, security-minded, and data validation testing
• Lead, mentor, and prioritize the work of QA and Data Quality Analysts, setting standards, coaching on technique, and reviewing test deliverables
• Establish release quality gates, entry/exit criteria, and go/no-go recommendations for production deployments across all environments
• Oversee validation of claims and premium BDX ingestion, transformation, reconciliation, and aggregation against Lloyd’s reporting standards and client specifications
• Verify financial calculations including reserves, paid, incurred, outstanding, and adjustments, and ensure reconciliation of source files to transformed outputs
• Architect and maintain automated test frameworks for UI, API, and data pipelines, integrated into CI/CD (GitHub Actions) as automated quality gates
• Apply 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 validation
• Evaluate and validate AI-enabled product features, including accuracy, consistency, bias, and regression of LLM or ML outputs, using defined evaluation datasets and acceptance criteria
• Define the governance for responsible AI use in QA, including human review, data privacy, prompt and output traceability, and audit-ready evidence
• Own defect management and triage with engineering: severity and priority standards, root-cause analysis, and trend reporting
• Build and report quality metrics (coverage, defect escape rate, automation rate, data accuracy and reconciliation pass rates) to the Director of Engineering and leadership
• Drive shift-left practices: review requirements and designs, define acceptance criteria, and embed quality in Agile ceremonies
• Plan and coordinate regression, integration, performance, and UAT cycles with product, client, and delivery teams
• Maintain test data management, environment readiness, and audit-ready test documentation and control frameworks

Key Skills & Expertise

Quality Leadership & Strategy

• Proven experience leading QA teams or acting as the senior QA owner across software and data validation
• Ability to build test strategy, quality gates, and metrics programs from the ground up
• Strong risk-based test planning and prioritization under delivery pressure

Modern QA & AI Skills

• Hands-on use of AI coding and testing assistants (e.g., Claude, GitHub Copilot) for test design, test data generation, code review, and defect analysis
• Experience with AI-assisted or agentic test automation, including self-healing locators and automated test maintenance
• Skilled prompt engineering, and the ability to validate and govern AI-generated tests and outputs rather than trust them blindly
• Experience testing AI/LLM-enabled features: evaluation datasets, output scoring, regression of model behavior, and hallucination and bias checks
• Familiarity with ML-based anomaly detection and data profiling for data quality monitoring

Test Automation & Technical Skills

• Strong web application and API test automation experience (e.g., Playwright, Cypress, Selenium, Postman)
• Strong SQL skills (SQL Server) for data interrogation and reconciliation
• Working knowledge of Python, PowerShell, or similar scripting languages
• Experience integrating automated tests into CI/CD pipelines (GitHub Actions) and working with Azure-based environments
• Experience with performance and load testing tools (e.g., k6, JMeter) preferred
• Experience with JIRA and Confluence

Insurance & Data Domain

• Experience with Lloyd’s of London data, managing agents, or delegated authority reporting preferred
• Understanding of claims, risk, or premium bordereaux structures and FCP/market reporting workflows
• Proven experience validating financial and actuarial-related data and reconciling large datasets

Professional Skills

• Meticulous documentation and audit-ready testing practices
• Ability to challenge assumptions and question questionable data or results
• Strong communication with technical and business stakeholders, including influencing release decisions
• Coaching mindset with the ability to develop and hold a team to a high standard

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Finance, or related field
• 7 years of experience in QA, test automation, or data validation, including 2 years leading or mentoring a QA team
• Demonstrated experience applying AI tools to QA workflows in a production environment
• Advanced SQL proficiency and experience with test automation frameworks
• Experience working in Agile/Scrum environments
• Experience with insurance, reinsurance, or Lloyd’s data environments preferred
• Exposure to regulated financial or insurance systems strongly preferred

What We Offer

• A fast-paced environment with high visibility and impact
• A collaborative team with a shared focus on excellence and accountability
• Opportunity to build and lead the quality function at a growing technology firm, with the mandate to shape our AI-enabled QA practice
• A culture rooted in respect, transparency, and ownership