Job description

Description Keeper Security is hiring a Senior Software Development Engineer in Test (SDET), AI & Automation to join our AI team and help build a modern, automated approach to quality across AI-powered products and services. This is a 100% remote position, with an opportunity to work a hybrid schedule for candidates based in the El Dorado Hills, CA or Chicago, IL metro areas. Keeper’s cybersecurity software is trusted by millions of people and thousands of organizations globally. Keeper is published in 23 languages and sold in over 150 countries. Join one of the fastest-growing cybersecurity companies and help establish scalable quality engineering practices for AI-driven systems operating in security-sensitive environments. About Keeper Keeper Security is one of the fastest-growing cybersecurity software companies that protects thousands of organizations and millions of people in over 150 countries. Keeper is a pioneer of zero-knowledge and zero-trust security built for any IT environment. Its core offering, KeeperPAM®, is an AI-enabled, cloud-native platform that protects all users, devices and infrastructure from cyber attacks. Recognized for its innovation in the Gartner Magic Quadrant for Privileged Access Management (PAM), Keeper secures passwords and passkeys, infrastructure secrets, remote connections and endpoints with role-based enforcement policies, least privilege and just-in-time access. Learn why Keeper is trusted by leading organizations to defend against modern adversaries at KeeperSecurity.com. About the Job As a Senior SDET, AI & Automation, you will serve as an embedded quality engineering partner within Keeper’s AI team. You will work alongside engineers and Product throughout design and development to define test strategy, establish acceptance criteria and build automated coverage as AI-powered capabilities are being developed. This role requires experience testing both traditional deterministic software systems and non-deterministic AI/ML systems. Traditional application behavior can often be validated against consistent expected outputs, while AI models may produce different but acceptable results across models, prompts and inputs. You will help design testing approaches that account for this variability while still establishing measurable quality, reliability and safety standards. You will build automation frameworks, develop deterministic and probabilistic validation strategies, integrate testing into CI/CD workflows and help Keeper move toward continuous quality engineering rather than end-of-cycle QA. Responsibilities Partner directly with AI engineers, Software Engineers and Product Managers during design and development to define test strategy, acceptance criteria and automation requirements Design and maintain automated testing frameworks for AI-powered applications, backend services, APIs and supporting software systems Develop testing strategies for both deterministic software behavior and non-deterministic AI/ML outputs Define measurable evaluation criteria, tolerances and quality thresholds for AI model and LLM-driven functionality Build automated regression, integration, API and end-to-end coverage alongside feature development Develop test harnesses and evaluation workflows for prompts, models, agents, tool-calling workflows and AI-integrated applications Validate AI behavior across different models, prompts, inputs and system configurations Develop automated test utilities using languages such as Python, Java, JavaScript/TypeScript, Rust or similar technologies Integrate automated validation and quality gates into CI/CD pipelines using GitHub Actions, Jenkins, GitLab CI or similar platforms Build and maintain test datasets, mocks, fixtures and synthetic data required for repeatable AI and software validation Analyze model and application failures to distinguish defects, expected model variability, data issues and test instability Evaluate AI outputs for reliability, consistency, safety and alignment with expected product behavior Work with engineering teams to improve application testability, observability and diagnostic capabilities Track test cases, execution results and coverage using TestRail or similar test management platforms Analyze logs, telemetry and system behavior to identify root causes and produce clear, reproducible defect reports Reduce flaky tests and improve the speed, stability and maintainability of automated test suites Contribute to quality engineering standards, AI testing methodologies and automation best practices across Keeper’s AI organization Use AI-assisted tools such as Claude, ChatGPT, GitHub Copilot or similar platforms to improve automation development, test generation, debugging, analysis and documentation Requirements 5+ years of experience in SDET, software development, test automation or another code-intensive quality engineering role Hands-on experience testing AI/ML, LLM-powered or model-integrated software systems Strong understanding of the differences between deterministic software testing and non-deterministic AI/ML validation Experience defining evaluation criteria, expected behaviors, tolerances or scoring approaches for AI-driven functionality Must know automation frameworks, like Playwright & Pytest Strong programming skills in Python, Java, JavaScript/TypeScript, Rust or another general-purpose programming language Significant experience designing, developing and maintaining automated test frameworks Experience building automated functional, integration, API and end-to-end test coverage Experience testing REST APIs and distributed application workflows using tools such as Postman, REST Assured or similar platforms Experience integrating automated tests into CI/CD pipelines using GitHub Actions, Jenkins, GitLab CI or similar technologies Experience working within an Agile software development team with close collaboration between QA, Engineering and Product Strong understanding of shift-left testing, continuous quality and testability principles Experience with TestRail or similar test management platforms Strong debugging and troubleshooting skills using logs, APIs, application telemetry and development tools Experience with Git-based development workflows, code review and modern software engineering practices Familiarity with AI-assisted development and testing tools such as Claude, ChatGPT, GitHub Copilot or similar technologies Strong analytical and problem-solving skills with the ability to evaluate variable AI behavior without relying solely on exact-match outcomes Strong written and verbal communication skills and ability to collaborate closely with AI engineers, Software Engineers, Product Managers and QA professionals Bachelor’s degree in Computer Science, Engineering or a related technical field, or equivalent practical experience Due to this role’s involvement with FedRAMP compliance requirements, qualified candidates must be a U.S. Person, defined as a U.S. citizen or lawful permanent resident. Preferred Qualifications Experience testing LLMs, agentic systems, retrieval-augmented generation, tool calling or prompt-driven workflows Experience building automated model evaluation, benchmarking or regression frameworks Familiarity with AI evaluation metrics and techniques for measuring quality across non-deterministic outputs Experience with Rust in production or test automation environments Experience with performance, reliability, security or adversarial testing of AI-enabled systems Experience with AI-assisted generation of automated tests or synthetic test data Familiarity with Docker, Kubernetes or cloud-based testing environments Experience testing cybersecurity, identity, PAM or other security-sensitive software Experience building shared automation frameworks or internal testing tools used across engineering teams Benefits Medical, Dental & Vision (inclusive of domestic partnerships Employer Paid Life Insurance & Employee/Spouse/Child Supplemental life Voluntary Short/Long Term Disability Insurance 401K (Roth/Traditional) A generous PTO plan that celebrates your commitment and seniority (including paid Bereavement/Jury Duty, etc) Keeper Security, Inc. is an equal opportunity employer and participant in the U.S. Federal E-Verify program. We celebrate diversity and are committed to creating an inclusive environment for all employees. Classification: Exempt Keeper Candidate Privacy Notice This notice explains how Keeper Security processes your personal data during recruitment. Depending on the role and location, the Controller of personal data (the organization responsible for determining why and how personal data is processed) will be Keeper Security Inc. (US), Keeper Security EMEA Ltd. (Ireland), or Keeper Security APAC K.K (Japan). 1. Data We Collect Information You provide: Contact details, CV/resume, cover letter Employment history, qualifications, work eligibility Application responses and uploaded documents Information We generate: Interview notes, assessments, communications Scheduling information Information From Others: Recruiter/referral information who submit your profile References (with your consent, before final offer) Public professional profiles Background verification (post offer) Voluntary Diversity and Equal Opportunity Information We may ask you to voluntarily provide diversity information including race/ethnicity, gender, disability status and veteran status (US). Providing this information is optional and Keeper collects this data in order to comply with EEOC and similar requirements 2. How We Use Your Data Assess your application and suitability Manage interviews and recruitment workflow Consider you for other/future roles (we may seek your consent to keep your information on our systems beyond the retention period specified) Comply with employment law obligations 3. Legal Basis Legitimate Interests (recruitment management, security and integrity of the hiring process) Contracting steps (for progressed candidates) Legal and regulatory compliance obligations; explicit consent where required 4. Who We Share Information With Internal: HR, hiring managers, interviewers*, IT support for system administration *Note - diversity and equal opportunity data is not shared with hiring managers. Third Parties: Service providers who assist with: Applicant tracking, recruitment systems and assessment providers Background verification vendors (post offer) Recruitment agencies (where applicable) Tools to support communication, collaboration and to securely store your data Keeper ensures that all our third parties are contractually bound to protect your personal data with adequate safeguards in place. 5. International Transfers Your data may be accessed by Keeper entities globally as needed for the purposes of hiring and decision making. We protect any such data transfer between Keeper entities using appropriate safeguards under applicable data protection laws. 6. Security We implement appropriate technical and organizational measures to protect your data, consistent with our industry leading security standards. 7. Retention We keep your data for 24 months from your last application activity, then delete or anonymize it. Exceptions: You opt into our talent database for further retention by providing consent (extended retention) You're hired (transfers to employee records) 8. Your Rights You have the following rights and can contact us at the email below to exercise them: Access, correct, or delete your data, subject to applicable law and retention requirements Object to or restrict processing Withdraw consent (where applicable) Request data portability Lodge a complaint with your data protection authority If you become an employee, your rights regarding your employee record are governed by our internal Employee Privacy Notice and certain data will be retained as required under relevant laws such as employment or tax law. When you request access to your personal data, some information may be redacted if it includes the personal data of other individuals or information that we must protect in order to preserve their privacy rights. 9. Automated Decisions Keeper does not make hiring decisions using solely automated processing. 10. Contact - Candidates can send privacy questions to: privacy@keepersecurity.com

Requirements

Must-haves

Partner directly with AI engineers, Software Engineers and Product Managers during design and development to define test strategy, acceptance criteria and automation requirements
Design and maintain automated testing frameworks for AI-powered applications, backend services, APIs and supporting software systems
Develop testing strategies for both deterministic software behavior and non-deterministic AI/ML outputs
Define measurable evaluation criteria, tolerances and quality thresholds for AI model and LLM-driven functionality
Build automated regression, integration, API and end-to-end coverage alongside feature development
Develop test harnesses and evaluation workflows for prompts, models, agents, tool-calling workflows and AI-integrated applications
Validate AI behavior across different models, prompts, inputs and system configurations
Develop automated test utilities using languages such as Python, Java, JavaScript/TypeScript, Rust or similar technologies
Integrate automated validation and quality gates into CI/CD pipelines using GitHub Actions, Jenkins, GitLab CI or similar platforms
Build and maintain test datasets, mocks, fixtures and synthetic data required for repeatable AI and software validation
Analyze model and application failures to distinguish defects, expected model variability, data issues and test instability
Evaluate AI outputs for reliability, consistency, safety and alignment with expected product behavior
Work with engineering teams to improve application testability, observability and diagnostic capabilities
Track test cases, execution results and coverage using TestRail or similar test management platforms
Analyze logs, telemetry and system behavior to identify root causes and produce clear, reproducible defect reports

Nice-to-haves

Experience testing LLMs, agentic systems, retrieval-augmented generation, tool calling or prompt-driven workflows
Experience building automated model evaluation, benchmarking or regression frameworks
Familiarity with AI evaluation metrics and techniques for measuring quality across non-deterministic outputs
Experience with Rust in production or test automation environments
Experience with performance, reliability, security or adversarial testing of AI-enabled systems
Experience with AI-assisted generation of automated tests or synthetic test data
Familiarity with Docker, Kubernetes or cloud-based testing environments
Experience testing cybersecurity, identity, PAM or other security-sensitive software
Experience building shared automation frameworks or internal testing tools used across engineering teams

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlci/cdllmapipythonjavajavascripttypescriptrustrestagiledockerkubernetes

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Pto