About PureFacts Financial Solutions

PureFacts is the leader in the Revenue Performance Management category for wealth and asset management firms. The PureRevenue™ Platform helps organizations maximize revenue potential by connecting pricing, billing, compensation, advisor behavior, and AI-powered intelligence within a single Revenue Book of Record. By transforming fragmented revenue processes into a coordinated growth system, firms gain greater visibility, stronger pricing discipline, improved revenue capture, and more effective advisor alignment. The result is faster organic growth, improved profitability, and increased enterprise value. For more than 25 years, PureFacts has helped leading financial institutions turn revenue from an operational process into a strategic advantage.

At PureFacts, we are building an AI-native platform and company. We embed AI, intelligent automation, and agentic workflows across our products and operations to detect anomalies, surface insights, streamline repetitive work, and support faster, better decision-making. In a highly regulated industry, we believe AI must be practical, governed, and auditable—amplifying human expertise while helping our teams and clients focus on higher-value, strategic work.

About the role

We are seeking a highly skilled and self-motivated Senior AI Test Automation Engineer to join our Quality Engineering team. The ideal candidate will have extensive experience in test automation, database validation, AI-assisted testing, and modern quality engineering practices. This role requires expertise in building scalable automation frameworks, validating complex data migrations, and leveraging AI-enabled tools to improve productivity, accelerate testing cycles, enhance test coverage, and continuously improve software quality.

The successful candidate will play a key role in driving AI-powered quality engineering practices, championing innovation, and ensuring the effective use of AI technologies while maintaining high standards of quality, security, compliance, and reliability.

What you'll do

• Design, develop, and maintain scalable automation frameworks using Java, Python, and Playwright.
• Develop and execute automated functional, regression, integration, API, and end-to-end test suites.
• Perform comprehensive database testing, including data validation, data integrity, data consistency, and backend verification.
• Write and optimize complex SQL queries involving joins, subqueries, Common Table Expressions (CTEs), window functions, aggregates, and stored procedures to validate business rules and application data.
• Validate database transactions, triggers, stored procedures, views, functions, indexes, and constraints.
• Perform end-to-end validation of data across multiple databases and systems to ensure consistency and integrity.
• Validate ETL processes and data migration activities, ensuring accurate transformation, reconciliation, and completeness of migrated data.
• Perform source-to-target data validation for large-scale migration and integration projects.
• Create reusable SQL validation scripts to support automation and regression testing.
• Analyze database performance and identify data-related issues impacting application functionality.
• Validate data generated through APIs, batch jobs, scheduled processes, and background services.
• Perform backend testing by validating application data against business requirements.
• Execute performance, load, stress, security, and accessibility testing.
• Work with Snowflake to validate data, execute queries, verify data pipelines, and support reporting validation.
• Develop reusable automation utilities and testing libraries.
• Integrate automated tests into CI/CD pipelines to support continuous integration and continuous delivery.
• Utilize AI-assisted tools such as Microsoft Copilot, ChatGPT, Claude, Cursor, GitHub Copilot, and similar technologies to accelerate test design, automation development, defect analysis, SQL generation, troubleshooting, documentation, and productivity improvements.
• Leverage Generative AI solutions to create, optimize, and maintain test scenarios, test cases, test data, validation scripts, and quality engineering documentation.
• Evaluate, recommend, and adopt emerging AI-enabled testing capabilities that improve efficiency, coverage, risk detection, and release confidence.
• Validate and review AI-generated outputs to ensure accuracy, reliability, compliance, and alignment with business requirements.
• Contribute to AI testing standards, best practices, governance, and responsible use of AI within the Quality Engineering organization.
• Collaborate closely with developers, business analysts, DevOps, product teams, and business stakeholders throughout the software development lifecycle.
• Analyze application logs, troubleshoot defects, perform root cause analysis, and continuously improve test coverage.
• Create and maintain test strategies, test plans, test cases, automation scripts, SQL validation scripts, and technical documentation.
• Mentor junior team members on automation best practices, AI-assisted testing approaches, and quality engineering standards.
• Drive continuous improvement initiatives that leverage AI to improve software quality, delivery speed, and operational efficiency.

Qualifications

• Experience with enterprise applications, microservices, and distributed architectures.
• Experience with AWS or Azure cloud platforms.
• Experience with test data management and environment management.
• Experience working with large datasets and high-volume transactional systems.
• Experience leading or supporting AI transformation initiatives within Quality Engineering teams.
• Experience establishing AI testing standards, governance practices, and adoption frameworks.
• Knowledge of AI-driven testing platforms, intelligent test automation, and predictive quality analytics.
• ISTQB or equivalent QA certification.
• Self-motivated with the ability to work independently and take ownership of deliverables.
• Strong attention to detail and commitment to delivering high-quality software.
• Ability to manage multiple priorities in a fast-paced Agile environment.
• Passion for continuous learning, emerging technologies, and AI-enabled quality engineering practices.
• Strong curiosity and adaptability in evaluating and adopting new AI technologies.
• Ability to balance AI-assisted productivity with engineering judgment, critical thinking, and quality standards.
• Collaborative mindset with the ability to work effectively in cross-functional teams.
• Ability to champion innovation, continuous improvement, and AI adoption across the Quality Engineering organization.