Sr Software Engineer - AI-First Development - Las Vegas Sands

Job Description:

Position Overview

The primary responsibility of the Senior Software Engineer (AI-First Development) is to design, orchestrate, and validate software applications built through AI-driven development workflows. This is not an AI-assisted traditional developer role. Rather than writing the majority of code by hand, this role operates within an AI-First Software Development Lifecycle (SDLC) where AI agents serve as the primary producers of code, configuration, and test artifacts. The engineer provides architectural direction, context engineering, human-in-the-loop governance, and final accountability for all delivered software.

The Senior Software Engineer combines deep software engineering fundamentals with the ability to think in systems, design effective agent workflows, and validate AI-generated outputs across security, correctness, performance, and compliance dimensions.

All duties are to be performed in accordance with departmental and Las Vegas Sands Corp.’s policies, practices, and procedures. All Las Vegas Sands Corp. Team Members are expected to conduct and carry themselves in a professional manner at all times. Team Members are required to observe the company’s standards, work requirements and rules of conduct.

Essential Duties & Responsibilities

Agent Workflow Design and Orchestration

Design, build, and maintain AI agent workflows that produce application code, infrastructure configuration, test suites, and documentation.

Decompose complex application requirements into discrete, well-scoped tasks that AI agents can execute effectively within defined boundaries.

Select and configure appropriate AI models, agent frameworks, and tooling for each workflow based on task complexity, risk level, and cost considerations.

Construct and maintain context stores that provide agents with organizational knowledge, coding standards, architectural patterns, and domain context needed to produce correct and consistent outputs.

Author 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 sessions.

Design subagent architectures that decompose complex workflows into specialized, scoped agents with appropriate tool access, following the principle of least privilege for each agent role.

Apply 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 reliable.

Participate in Mob Elaboration sessions to collaboratively refine requirements, acceptance criteria, and context packages before agent execution begins.