Filevine is a Legal AI company delivering Legal Operating Intelligence for the future of legal work. Grounded in a singular system of truth, Filevine brings together data, documents, workflows, and teams into one unified platform—where modern legal work happens with clarity and consistency.
Powered by LOIS, the Legal Operating Intelligence System, Filevine connects context across every matter to transform legal operations from reactive to proactive. LOIS reads, understands, and reasons across your data to surface insight, automate complexity, and give professionals the clarity and confidence to see more, know more, and do more. Fueled by a team of exceptional collaborators and innovators, Filevine’s rapid growth has earned AI awards and recognition from Deloitte and Inc. as one of the most innovative and fastest-growing technology companies in the country.
Role Summary:
We are seeking a highly technical people leader to serve as our SDET Manager, responsible for guiding the strategy, architecture, and execution of the next generation of AI-augmented quality engineering across the organization. This role requires both deep hands-on expertise and strong leadership capability to scale a high-performing automation team while driving measurable improvements in reliability and product quality.
In addition to advancing traditional automation frameworks, this role will lead and support the adoption of AI-driven and agentic automation solutions to increase test intelligence, reduce operational friction, and accelerate quality feedback loops across the SDLC.
Responsibilities
Lead and mentor a team of SDETs and automation engineers, setting clear standards for technical excellence and deliveryDrive the strategy and implementation of AI-powered and agentic automation solutions to improve defect detection, test generation, test maintenance, and deployment validationEvaluate and integrate emerging AI tooling into the quality engineering ecosystem, ensuring scalable, secure, and measurable impact on release confidence and automation efficiencyLead and monitor reduction of change failure rates through improved test architecture, release validation, and deployment safeguardsExpand and optimize automated test coverage across UI, API, integration, and backend systemsPartner with cross-functional stakeholders to proactively identify risk and improve release stabilityChampion continuous improvement through root cause analysis, defect trend evaluation, and performance monitoringRemain hands-on when necessary, reviewing automation design, validating technical approaches, and guiding architectural decisionsDrive continuous improvement by identifying gaps in processes, tooling, and test coverage
Knowledge & Skills
Strong background in automation framework design and scalable test architectureDeep experience with modern automation tools such as Playwright, Selenium, Cypress, or similar platformsProficiency in object-oriented programming languages such as C# or PythonExperience validating distributed and integrated systems, including microservicesStrong understanding of CI/CD pipelines, version control systems, and DevOps practicesExperience implementing automated testing across multiple layers:API, integration, system, end-to-end, etc.Familiarity with Agile development methodologies and modern SDLC practicesAbility to align automation strategy with emerging technologies and evolving platform architecture
Qualifications
Proven experience leading quality or automation teams in a fast-paced engineering environment5+ years of managing distributed or remote quality teams10+ years of hands-on automation development experienceDemonstrated ability to influence cross-functional teams and senior stakeholdersStrong analytical mindset with the ability to translate quality metrics into business outcomesEffective communicator who can simplify complex technical topics for executive audiencesPractical experience designing or implementing AI-driven automation solutions, including intelligent test generation, self-healing frameworks, or agent-based validation systems Strong understanding of how large language models and agentic workflows can be leveraged within CI/CD pipelines to enhance quality signal, coverage optimization, and risk detection
