[Remote] Sr Software Engineer - 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 Engineer specialized in AI-First Development. The primary responsibility of this role is to design and validate software applications using AI-driven development workflows, ensuring quality and compliance through rigorous verification processes.ResponsibilitiesDesign, build, and maintain AI agent workflows that produce application code, infrastructure configuration, test suites, and documentationDecompose complex application requirements into discrete, well-scoped tasks that AI agents can execute effectively within defined boundariesSelect and configure appropriate AI models, agent frameworks, and tooling for each workflow based on task complexity, risk level, and cost considerationsConstruct and maintain context stores that provide agents with organizational knowledge, coding standards, architectural patterns, and domain context needed to produce correct and consistent outputsAuthor and maintain the agent toolchain, including Skills (SKILL.md) for reusable domain knowledge, hooks for deterministic automation at defined workflow points, and project memory files (CLAUDE.md, AGENTS.md) that provide persistent context across agent sessionsDesign subagent architectures that decompose complex workflows into specialized, scoped agents with appropriate tool access, following the principle of least privilege for each agent roleApply compound engineering practices that systematically capture insights, patterns, and failure modes from each development cycle, encoding them into project memory, skills, and agent configurations so that each unit of work makes subsequent work easier and more reliableParticipate in Mob Elaboration sessions to collaboratively refine requirements, acceptance criteria, and context packages before agent execution beginsApply a multi-layer verification framework to all AI-generated outputs, validating functional correctness, security posture, performance characteristics, code quality, and regulatory complianceEstablish and enforce human-in-the-loop (HITL), on-the-loop (OHOTL), and after-the-loop (AHOTL) governance checkpoints appropriate to the risk level of each workflowReview, test, and approve AI-generated code, ensuring it meets Sands coding standards, architectural guidelines, and security requirements before promotion to productionDesign and maintain automated verification pipelines that supplement human review, including test harnesses, static analysis gates, and runtime telemetryIdentify and remediate patterns of agent drift, hallucination, or quality degradation across repeated workflow executionsImplement agent observability and telemetry systems that track agent behavior, tool call patterns, token consumption, and output quality metrics across workflowsArchitect and deliver full-stack applications across web, API, and data layers using AI-First methodologies as the primary development approachDefine system architecture, data models, API contracts, and integration patterns that serve as the foundational context for agent-driven developmentCollaborate with cross-functional teams including product, design, infrastructure, and security to translate business requirements into executable agent workflowsCoordinate with development teams across global locations to ensure consistency in agent workflows, coding standards, and verification practicesMaintain the ability to write, debug, and refactor code directly when agent outputs require manual intervention or when exploring novel architectural approachesEnsure all delivered applications meet enterprise standards for scalability, maintainability, observability, and operational readinessDesign and build custom MCP servers that expose internal tools, databases, and business systems to AI agents through standardized interfaces, enabling agents to interact with enterprise data securely and reliablyEvaluate emerging AI models, agent frameworks, MCP servers, and development tools to continuously improve workflow effectiveness and output qualityMentor team members on AI-First development practices, context engineering techniques, and verification methodologiesContribute to the evolution of the Sands AI-First SDLC standard, proposing refinements based on practical experience and measurable outcomesDocument agent workflow patterns, prompt libraries, context store structures, and lessons learned to build institutional knowledgeMonitor and optimize token consumption and cost across agent workflows, implementing strategies such as plan mode, context editing, multi-session splitting, and efficient context window management to control operational expensesParticipate in Mob Construction sessions, guiding agent execution in real time and coaching team members on effective 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 policy7+ years of professional software development experience, with demonstrated progression into senior or lead roles1+ years of hands-on experience using AI-assisted development tools (such as GitHub Copilot, Cursor, Claude Code, Windsurf, or similar) as a core part of the daily development workflowStrong foundational knowledge across at least two major programming ecosystems (for example, .NET/C#, JavaScript/TypeScript, Python, Java, Go), with the ability to evaluate and validate AI-generated code in any language relevant to a given projectWorking knowledge of relational and non-relational databases, including data modeling, query optimization, and schema designExperience with cloud platforms (Azure preferred, AWS or GCP also acceptable), including deployment, configuration, and cost managementWorking knowledge of DevOps practices, CI/CD pipelines, and infrastructure-as-code conceptsExperience with containerization (Docker) and container orchestration (Kubernetes or similar)Demonstrated ability to conduct thorough code reviews, identify defects in AI-generated outputs, and provide 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 experienceExperience designing multi-agent and subagent architectures using frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or custom orchestration layers. Understanding of agent planning, tool use, memory, multi-step reasoning, and scoped tool access patternsPractical experience constructing structured context packages for LLMs, including prompt design, RAG pipelines, context window optimization, project memory files (CLAUDE.md, AGENTS.md), and integration with MCP servers. Understanding of tactical context management strategies such as plan mode, context editing, and multi-session splittingExperience authoring Skills (SKILL.md), configuring hooks for deterministic automation, building custom MCP servers, and assembling agent toolchains that enable repeatable, production-grade workflowsExperience implementing human-in-the-loop oversight models, automated evaluation pipelines, and strategies for detecting agent drift or hallucination. Familiarity with agent telemetry, token consumption monitoring, and cost governance across multi-agent workflowsExperience with microservices, event-driven architectures, or message-based systems (Kafka, RabbitMQ, Azure Service Bus). Understanding of enterprise integration patterns at scaleKnowledge of secure development practices, OWASP guidelines, and experience working within regulated industries (gaming, finance, hospitality, or similar). Understanding data privacy and responsible AI principlesExperience with unit testing, integration testing, end-to-end testing frameworks, and automated quality gates. Experience evaluating AI-generated test coverage and identifying gapsTrack record of mentoring developers, leading technical initiatives, and driving adoption of new development practices across teamsCompany 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.