Quality Assurance Lead

Quality Assurance LeadWe are seeking an experienced Quality Assurance Lead to lead quality planning and testing across software, data pipelines, analytics, AI outputs, accessibility, and deliverables for a Federal data analytics and AI modernization initiative.The team will deliver a secure, scalable platform that integrates structured and unstructured data, provides data visualization and traceable AI-assisted analytics, and gives examiners centralized tools for search, review, monitoring, and decision support. The platform will support professional judgment and will not replace authoritative agency financial or grants-management systems or execute financial transactions.Analytica has been recognized by Inc. Magazine as the fastest-growing private US small business. We work with U.S. government customers in health, civilian, and national security missions. As a core member you'll work with a diverse team of professionals to solve matters, architect nuisances, and come up with alternatives. We offer competitive compensation with opportunities for bonuses, employer paid health care, training and development funds, and 401k match.Quality Strategy & Test EngineeringDevelop and execute an end-to-end QA strategy spanning application functionality, data pipelines, analytics, AI-enabled capabilities, integrations, accessibility, and technical deliverables.Establish test plans, test cases, acceptance criteria, quality gates, and release-readiness standards across development, test, staging, and production environments.Lead functional, integration, system, regression, performance, security, accessibility, usability, and user-acceptance testing.Design and implement automated testing frameworks and integrate automated tests into CI/CD pipelines.Establish appropriate testing approaches for APIs, databases, data ingestion pipelines, user interfaces, and distributed services.Work with developers, data engineers, AI/ML engineers, platform engineers, and product owners to identify defects and quality risks early in the development lifecycle.Data & AI QualityEstablish data-quality testing for accuracy, completeness, consistency, validity, timeliness, uniqueness, and data integrity across ingestion and transformation pipelines.Develop validation approaches to ensure data is correctly transformed and represented in downstream analytics, visualizations, reports, and applications.Define testing strategies for analytical models, calculations, business rules, signals, and derived metrics.Establish quality controls for AI/LLM-enabled functionality, including output accuracy, consistency, relevance, traceability, reliability, and appropriate handling of edge cases.Develop repeatable evaluation approaches for AI outputs and identify potential hallucinations, unsupported conclusions, data leakage, or other unacceptable behavior.Validate that AI-generated insights can be traced back to appropriate underlying data and that the platform clearly distinguishes AI-assisted analysis from authoritative source information.Test model and AI-service changes to ensure new versions do not introduce regressions in existing functionality or analytical results.Required Qualifications7+ years of experience in software quality assurance, quality engineering, test automation, or a related discipline, with experience leading QA strategy for enterprise systems.Demonstrated experience developing and implementing end-to-end QA strategies for complex software, data, analytics, or AI-enabled platforms.Hands-on experience with automated testing and functional, integration, regression, performance, security, accessibility, and user-acceptance testing.Experience testing APIs, databases, web applications, data pipelines, and distributed services.Experience developing automated tests and integrating them into Agile/DevSecOps CI/CD pipelines.Experience with defect management, root-cause analysis, requirements traceability, test coverage, quality metrics, and release-readiness reporting.Experience developing data-quality validation and testing approaches for data ingestion, transformation, and analytics.Experience testing or evaluating AI/ML or LLM-enabled applications, including validation of AI-generated outputs and analytical results.Understanding of software development lifecycle, Agile methodologies, CI/CD, and modern application architectures.Familiarity with technologies such as Linux, PostgreSQL or Microsoft SQL Server, Java or.NET, Jenkins, self-hosted Azure DevOps, Kubernetes/Rancher, APIs, and open-source AI models.Strong analytical, problem-solving, communication, and technical documentation skills.Ability to work effectively with developers, data engineers, AI/ML engineers, cybersecurity professionals, product owners, and Government stakeholders.U.S. citizenship and ability to obtain and maintain Top Secret eligibility, as required for all contractor personnel supporting the effort.Active Top Secret highly preferred.Preferred QualificationsExperience supporting Federal financial management, budget execution, grants management, payment systems, award oversight, financial reporting, or financial stewardship is preferred.Experience supporting Federal financial management, grants, payment, or award-oversight platforms.