Sr Software Development Engineer in Test - AI-First Development
Test Strategy, Agent Workflow Design, and Orchestration
Design, build, and maintain AI agent workflows that produce unit, integration, end-to-end, performance, and security test suites from specifications and intent documents.
Decompose acceptance criteria and technical contracts into discrete, verifiable test scenarios that AI agents can execute effectively within defined boundaries.
Select and configure appropriate AI models, agent frameworks, and test-generation tooling for each workflow based on risk level, coverage requirements, and cost considerations.
Construct and maintain test context that provides agents with test patterns, fixture strategies, data classification rules, and domain information needed to produce correct and consistent test outputs.
Contribute to the testing toolchain, including reusable test skills, automation hooks, and project memory files that provide persistent context across agent sessions.
Authoring of advanced toolchain components may be developed on the job.
Systematically capture defect patterns, escape modes, and verification failures from each development cycle and encode them back into shared context, test skills, and agent configurations so that subsequent work becomes more reliable.
Participate in collaborative refinement sessions to align on acceptance criteria, technical contracts, and test context packages before agent execution begins.
Verification and Quality Assurance
Operate the multi-layer Verification Framework on every pull request, with primary ownership of the automated testing layer, validating functional correctness, security posture, performance characteristics, code quality, and regulatory compliance.
Apply human oversight at governance checkpoints appropriate to the risk level of each workflow, including pre-execution review, in-flight observation, and post-execution audit.
Review, test, and approve AI-generated code and test suites, ensuring they meet Sands testing standards, architectural guidelines, and security requirements before promotion to production.
Verify that AI-generated tests exercise specified intent rather than mirroring implementation, and reject suites that pass without actually exercising the behavior the specification asked for.
Support independent QA verification after merge, contributing to system, integration, and regression testing in production-like environments and partnering with the QA Lead on User Acceptance Testing coordination where applicable.
Support agent observability practices that track test behavior, flakiness signals, coverage trends, and defect escape rates across workflows.
Test Engineering and Architecture
Architect and deliver scalable test automation frameworks across web, API, mobile, and data layers using AI-First methodologies as the primary development approach.
Define test data strategies, test environment patterns, and verification contracts that serve as foundational context for agent-driven test generation.
Collaborate with cross-functional teams including engineering, product, infrastructure, and security to translate business requirements into executable verification workflows.
Capture and share lessons learned to build institutional knowledge.
Write, debug, and refactor test code directly when agent outputs require manual intervention or when designing novel test approaches.
Ensure delivered test automation meets enterprise standards for reliability, maintainability, observability, and operational readiness.
Continuous Improvement and Mentorship
Evaluate emerging AI models, agent frameworks, and test automation tools to continuously improve verification effectiveness and output quality.
Mentor team members on AI-assisted testing practices, context engineering techniques, and verification methodologies.
Document test patterns, prompt and context libraries, and lessons learned to build institutional knowledge.
Perform job duties in a safe manner.
Attend work as scheduled on a consistent and regular basis.
Perform other related duties as assigned.