代理AI软件工程师
Agentic AI Software Engineer
TCP致力于打造一个多元化和包容性的团队。然而,我们无法为该职位提供签证支持。
关于TCP(TimeClock Plus):
30多年来,TCP通过提供灵活、移动的考勤管理和劳动力管理解决方案,帮助组织更好地与员工互动。数以万计的客户和数百万用户信赖TCP,TCP为公共和私营部门的各种规模的组织提供一流的科技和个性化支持,以满足其复杂的考勤、员工排班、休假管理和其他劳动力需求。我们正在快速发展,对未来成功的愿景清晰明确——我们希望您加入我们的旅程!有关TCP的更多信息,请访问或在LinkedIn或Facebook上关注我们。
作为Agentic AI软件工程师,您将:
· 在跨职能敏捷环境中,从检测和决策逻辑到安全操作执行,端到端地设计、构建和交付Agentic AI功能
· 通过确定性规则引擎和受控数据来规范代理行为,使每个代理都能解释其推理过程,并且永远不会超出允许的边界
· 构建和运营LLM层,包括提示架构、结构化输出、置信度评分、超时设置和仅规则的回退路径
· 实现代理操作的安全模式,包括幂等操作、撤销窗口、带退避的重试以及不可变的审计日志
· 开发统计检测和基线逻辑,将劳动力数据转化为具有业务影响的排名可解释结果
· 管理从开发到生产阶段的推理成本、延迟和模型选择
· 与QA合作进行评估套件、影子模式发布以及每项代理功能的可信度指标,并在此过程中指导初级工程师
· 独立运作,设定优先级和目标,同时继续学习和提升技术能力
我们的技术栈:
- 后端:现代.NET和.NET Framework上的C#,采用多层服务架构。
- 前端:JavaScript和AngularJS,带有Jasmine单元测试。
- 数据库:Microsoft SQL Server,包括模式项目和幂等迁移脚本。
- 部署:Docker、Jenkins CI/CD和云托管部署。
要求
- 6年以上专业软件开发经验,包括将LLM支持或Agentic功能交付到生产环境。
- 在C#/.NET、SQL Server和API设计方面有深入的生产经验,在系统中需要处理高并发和复杂逻辑。
查看英文原文
TCP is committed to cultivating a diverse and inclusive team. However, we are not able to sponsor visas for this role.
About TCP (TimeClock Plus):
For more than 30 years, TCP has helped organizations engage their people by providing flexible, mobile timekeeping and workforce management solutions. Trusted by tens of thousands of customers and millions of users, TCP delivers best-in-class technology and personalized support to organizations of all sizes in the public and private sector to meet their complex timekeeping, employee scheduling, leave management and other workforce needs. Growth is happening and our vision for a successful future is clear – We’d love for you to join us on this journey! For more information on TCP, visit or follow us on LinkedIn or Facebook.
As an Agentic AI Software Engineer you will:
· Design, build, and ship agentic AI features end to end, from detection and decision logic through safe action execution, in a cross-functional agile environment
· Ground agent behavior in deterministic rules engines and governed data so every agent explains its reasoning and never acts outside permitted boundaries
· Build and operate the LLM layer, including prompt architecture, structured outputs, confidence scoring, timeouts, and rules-only fallback paths
· Implement safe patterns for agent actions, including idempotent operations, undo windows, retries with backoff, and immutable audit logging
· Develop statistical detection and baseline logic that turns workforce data into ranked, explainable findings with business impact attached
· Manage inference cost, latency, and model selection from development through production
· Partner with QA on evaluation suites, shadow-mode rollouts, and the trust metrics that gate every agent capability, and mentor junior engineers along the way
· Operate independently, setting priorities and goals while continuing to learn and grow technically
Our Technology Stack:
- Backend: C# on modern .NET and .NET Framework in a multi-tier service architecture.
- Frontend: JavaScript and AngularJS, with Jasmine unit tests.
- Database: Microsoft SQL Server, including schema projects and idempotent migration scripts.
- Delivery: Docker, Jenkins CI/CD, and cloud-hosted deployment.
Requirements
- 6+ years of professional software development experience, including shipping LLM-backed or agentic features to production.
- Deep production experience with C#/.NET, SQL Server, and API design in systems where correctness has financial consequences, such as payroll, billing, or banking.
- Experience integrating LLM APIs into enterprise applications, with structured outputs, retrieval grounding, and evaluation-driven iteration.
- Working fluency with statistical techniques on time-series data, such as rolling baselines, outlier detection, and threshold tuning.
- The ability to understand requirements and solve technical issues without supervision, serving as a technical lead.
AI Experience Requirements:
- Hands-on daily use of AI coding assistants or agentic tools, such as Claude Code, GitHub Copilot, or Cursor.
- Production experience with LLM APIs, MCP servers, or internal AI tooling.
- An understanding of human-in-the-loop agent design and write-capable AI.
- A clear understanding of LLM failure modes, including hallucination, prompt injection, and cost overrun, plus the limits and risks of AI-generated code.
- Preferred: experience with multi-agent orchestration, evaluation harness design, or statistical anomaly detection.
Physical Requirements:
- Prolonged periods sitting at a desk and working on a computer.
- Must be able to lift up to 15 pounds at times.
Benefits
- Competitive salary
- 20 Days of PTO (Paid Time Off) and 13 days of companywide holidays
- 8 hours to volunteer and impact the community
- Comprehensive benefits (Health/Dental/Vision/ 401K)
- Employee Choice Pre-Tax Benefit
TCP is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Originally posted on Himalayas