[Remote] Sr Software Development Engineer in Test - AI-First Development

Note: The job is a remote job and is open to candidates in USA. Las Vegas Sands Corp. is seeking a Senior Software Development Engineer in Test (AI-First Development) to design and validate automated verification systems within an AI-First Software Development Lifecycle. The role involves creating AI agent workflows, ensuring software quality through verification and quality assurance, and mentoring team members on AI-assisted testing practices.ResponsibilitiesDesign, build, and maintain AI agent workflows that produce unit, integration, end-to-end, performance, and security test suites from specifications and intent documentsDecompose acceptance criteria and technical contracts into discrete, verifiable test scenarios that AI agents can execute effectively within defined boundariesSelect and configure appropriate AI models, agent frameworks, and test-generation tooling for each workflow based on risk level, coverage requirements, and cost considerationsConstruct 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 outputsContribute 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 jobSystematically 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 reliableParticipate in collaborative refinement sessions to align on acceptance criteria, technical contracts, and test context packages before agent execution beginsOperate 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 complianceApply human oversight at governance checkpoints appropriate to the risk level of each workflow, including pre-execution review, in-flight observation, and post-execution auditReview, test, and approve AI-generated code and test suites, ensuring they meet Sands testing standards, architectural guidelines, and security requirements before promotion to productionVerify that AI-generated tests exercise specified intent rather than mirroring implementation, and reject suites that pass without actually exercising the behavior the specification asked forSupport 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 applicableSupport agent observability practices that track test behavior, flakiness signals, coverage trends, and defect escape rates across workflowsArchitect and deliver scalable test automation frameworks across web, API, mobile, and data layers using AI-First methodologies as the primary development approachDefine test data strategies, test environment patterns, and verification contracts that serve as foundational context for agent-driven test generationCollaborate with cross-functional teams including engineering, product, infrastructure, and security to translate business requirements into executable verification workflowsCoordinate with QA and engineering teams across global locations to ensure consistency in testing standards and verification practicesWrite, debug, and refactor test code directly when agent outputs require manual intervention or when designing novel test approachesEnsure delivered test automation meets enterprise standards for reliability, maintainability, observability, and operational readinessEvaluate emerging AI models, agent frameworks, and test automation tools to continuously improve verification effectiveness and output qualityMentor team members on AI-assisted testing practices, context engineering techniques, and verification methodologiesDocument test patterns, prompt and context libraries, and lessons learned to build institutional knowledgeParticipate in collaborative construction sessions, guiding agent execution in real time and coaching team members on effective test orchestration techniquesPerform job duties in a safe mannerAttend work as scheduled on a consistent and regular basisPerform other related duties as assignedSkillsAt least 21 years of ageProof of authorization to work in the United StatesBachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent professional experienceMust be able to obtain and maintain any certification or license, as required by law or policy5+ years of professional software development or test automation experience, including time in senior or lead positions where the candidate owned the design and delivery of non-trivial verification systemsDemonstrated daily use, over the past 6 months or more, of at least one modern AI-assisted development tool such as Claude Code, Cursor, GitHub Copilot, or Windsurf, with the ability to speak concretely about effective usage patterns and failure modesStrong foundational knowledge in at least one major programming ecosystem (such as .NET/C#, JavaScript/TypeScript, Python, Java, or Go) and hands-on experience with at least one modern test automation framework (such as Playwright, Cypress, REST Assured, pytest, or comparable). Familiarity with additional layers (UI, API, integration) is a plusExperience deploying and operating test automation on at least one major cloud platform (Azure, AWS, or GCP). Azure experience is a plus given the LVS footprint but is not requiredWorking knowledge of DevOps practices and CI/CD pipelines, including familiarity with how automated test gates fit into a build pipelineDemonstrated experience conducting thorough code reviews, identifying defects in both human- and AI-generated outputs, and providing constructive technical feedbackExcellent written and verbal communication skills, with the ability to articulate technical decisions and trade-offs to both technical and non-technical stakeholdersStrong interpersonal skills with the ability to communicate effectively and interact appropriately with management, other Team Members and outside contacts of different backgrounds and levels of experiencePractical experience constructing structured context for LLMs, including prompt design, RAG pipelines, context window optimization, project memory files (such as CLAUDE.md or AGENTS.md), and integration with MCP servers. Familiarity with tactical context management techniques such as plan mode, context editing, and multi-session splittingExperience authoring reusable skills, configuring automation hooks, building custom MCP servers, or otherwise assembling agent toolchains that enable repeatable, production-grade test workflowsExposure to one or more specialized testing approaches such as performance and load testing (K6, JMeter, Gatling), contract testing, mutation testing, or chaos engineering. Proficiency in any one is a plus; depth across all is not expectedKnowledge of secure testing practices, OWASP guidelines, and SAST/DAST/SCA tooling, and experience working within a regulated industry such as gaming, finance, healthcare, or hospitality. Understanding of data privacy and responsible AI principlesWorking knowledge of relational or non-relational databases sufficient to model test data, design verification queries, and reason about query performanceCompany OverviewFounded in 1990, Las Vegas Sands is the preeminent developer and operator of world-class integrated resorts that drive valuable business and leisure tourism in the regions where we operate. It was founded in 1990, and is headquartered in Las Vegas, Nevada, USA, with a workforce of 10001+ employees. Its website is https://www.sands.com.