AI工程师
AI Engineer
最低年薪 150,000 美元。最高年薪 175,000 美元。
职位概述
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角色范围：
AI 工程师制定标准、工具和控制措施，帮助 S:US 将 AI 解决方案从实验阶段转化为可靠的应用。该职位向 Apps, Data & AI 副总裁汇报，与 IT 部门合作，交付安全、可重用且成本效益高的 AI 能力，以支持 S:US 的使命。
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主要职责：
AI 工程与平台开发
- 构建和改进 AI 开发环境，包括 GitHub、VS Code、GitHub Copilot、Azure、代理和已批准的集成。
- 设计代理工作流、多代理协作、MCP 集成、测试和评审的可重用模式。
- 评估新兴的 AI 开发工具，并推荐适合 S:US 的 Microsoft 优先环境的工具。
- 将 AI 解决方案与企业平台和 API 集成，确保端到端的工作流可靠运行。
质量、安全与负责任的 AI
- 构建 AI 生成输出的测试和评估实践，包括自动化检查和对高风险变更的人工审核。
- 在代理工作流和 AI 工具中应用负责任的 AI、隐私和安全要求。
- 通过适当的访问、屏蔽、删除和审批控制措施，保护 PHI 和其他敏感的客户、员工和业务数据。
- 与 IT 运营和安全团队合作，管理提示注入、权限、第三方工具、密钥和软件供应链风险。
DevSecOps、监控与成本管理
- 使用 GitHub Actions、Azure DevOps 和 Azure 构建和加强 CI/CD 管道。
- 在软件交付过程中嵌入自动化测试、安全扫描和质量检查。
- 监控代理性能、可靠性、延迟、令牌使用和成本。
- 利用性能和成本数据优化模型、工作流和平台决策。
协作与赋能
- 与 Applications、Data、Analytics、IT 基础设施与安全以及 PMO 合作，应用共享的 AI 标准并提升交付能力。
- 创建实用的指南、培训和办公时间，帮助团队有效使用 AI 工程工具。
- 将新兴的 AI 能力转化为清晰的建议、标准和实践，供团队采用。
职位要求
必备资格
- 在基于云的环境中拥有五年或以上专业软件工程经验。
- 具有构建代理 AI 解决方案的实际经验，包括代理工作流、提示设计以及工具或 API 的使用。
查看英文原文
Min
USD $150,000.00/Yr.Max
USD $175,000.00/Yr.Position Overview
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SCOPE OF ROLE:
The AI Engineer builds the standards, tools, and controls that help S:US move AI solutions from experimentation into reliable use. Reporting to the Vice President, Apps, Data & AI, this role partners across IT to deliver secure, reusable, and cost-effective AI capabilities that support the S:US mission.
· KEY RESPONSIBILITIES:
AI Engineering & Platform Development
- Build and improve the AI development environment including GitHub, VS Code, GitHub Copilot, Azure, agents, and approved integrations.
- Design reusable patterns for agent workflows, multi-agent coordination, MCP integrations, testing, and review.
- Evaluate emerging AI development tools and recommend those that fit S:US’s Microsoft-first environment.
- Integrate AI solutions with enterprise platforms and APIs so workflows operate reliably from end to end.
Quality, Security & Responsible AI
- Build testing and evaluation practices for AI-generated output, including automated checks and human review for higher-risk changes.
- Apply responsible AI, privacy, and security requirements to agent workflows and AI tools.
- Protect PHI and other sensitive client, employee, and business data through appropriate access, masking, redaction, and approval controls.
- Partner with IT Operations & Security to manage prompt injection, permissions, third-party tools, secrets, and software supply chain risks.
DevSecOps, Monitoring & Cost Management
- Build and strengthen CI/CD pipelines using GitHub Actions, Azure DevOps, and Azure.
- Embed automated testing, security scanning, and quality checks into the software delivery process.
- Monitor agent performance, reliability, latency, token usage, and cost.
- Use performance and cost data to improve models, workflows, and platform decisions.
Collaboration & Enablement
- Partner with Applications, Data, Analytics, IT Infrastructure & Security, and PMO to apply shared AI standards and improve delivery.
- Create practical playbooks, training, and office hours that help teams use AI engineering tools effectively.
- Translate emerging AI capabilities into clear recommendations, standards, and practices that teams can adopt.
Job Requirements
REQUIRED QUALIFICATIONS
- Five or more years of professional software engineering experience in cloud-based environments.
- Hands-on experience building agentic AI solutions, including agent workflows, prompt design, and tool or API integrations.
- Strong knowledge of Microsoft Azure and experience with GitHub Actions or Azure DevOps.
- Experience building secure CI/CD pipelines with automated testing, security scanning, and quality checks.
- Experience evaluating AI output and applying responsible AI, privacy, and security controls.
- Strong full-stack engineering, API integration, automated testing, version control, and code review skills.
- Working knowledge of observability and monitoring tooling (Azure Monitor, Application Insights) and delivery/issue-tracking platforms (e.g., Jira).
Excellent communication and collaboration skills, with the ability to turn emerging AI capabilities into practical solutions.
PREFERRED QUALIFICATIONS
- Experience with LLMOps or agent observability tooling, including tracing, token spend monitoring, and model routing/fallback, in a production setting.
- Experience in a regulated enterprise technology environment, including direct exposure to PHI-handling or HIPAA compliance requirements.
- Familiarity with Jira or similar modern agile delivery tooling used to plan, track, and orchestrate engineering work.
- Experience standing up an AI or platform engineering capability from the ground up, ideally as an early or founding technical hire.
Company Overview
S:US IS AN EQUAL OPPORTUNITY EMPLOYER
Join a team of employees who care about the wellbeing of others. We believe in fostering a culture built on our core values: respect, integrity, support, maximizing individual potential and continuous quality improvement. From health and wellness resources to generous PTO, professional development, and more, explore all that we offer on ourBenefits Page and see how S:US invests in you.
We believe in fostering a culture built on our core values: respect, integrity, support, maximizing individual potential and continuous quality improvement.
All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, age, sexual orientation, national origin, veteran status, or genetic information and including all other statuses protected by Federal, State and Local laws. S:US is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities, including allowance of the use of services animals. To request reasonable accommodation or if you believe such a request was improperly handled or denied, contact the Leave Team at .
ID
2026-18997Originally posted on Himalayas