AI工程师（生成式AI平台）
AI Engineer (GenAI Platform)
#### 公司简介
Experian 是一家全球数据和技术公司，为世界各地的个人和企业创造机会。我们在多个市场开展业务，包括金融服务、医疗保健、汽车、农业、保险等。Experian 投资于人才和先进的新技术，以释放数据的潜力。我们在 32 个国家拥有 25,200 名员工。
我们的独特之处在于重视你的价值。Experian 的以人为本、包容性和以目标为导向的文化获得了多项奖项——包括 2025 年世界最佳工作场所™（财富全球前 25 强）以及在 26 个国家获得的“最佳工作场所™”等。通过社交媒体上的 Experian Life 或浏览我们的职业网站，了解原因。Experian 还自豪地成为平等机会和积极行动雇主。
#### 职位描述
我们正在寻找一名 **AI 工程师（GenAI 平台）**，参与我们全球生成式人工智能平台的演进。
该职位将在设计、开发和运营支持各国工程和产品团队的 AI 服务中发挥关键作用，从而实现可扩展、安全、可观测且成本高效的 GenAI 解决方案。
该职位的重点是开发平台级别的生成式 AI 能力，包括代理系统、模型集成、LLMOps 和成本治理。这不是一个专注于从零开始训练或微调模型的职位。
主要职责
- 设计和开发生成式 AI 服务和多代理系统。
- 实现 RAG（检索增强生成）、工具调用和代理编排解决方案。
- 通过 LLM 网关集成和操作模型。
- 开发 LLMOps 实践，用于监控、可观测性和治理。
- 实现使用量测量、费用分摊和推理成本优化机制。
- 构建和维护支持计费和计量流程的数据管道。
- 应用 MLOps、CI/CD、自动化测试和模型生命周期管理实践。
- 处理事件、监控、可靠性及持续服务改进。
- 与全球的产品、工程、平台、安全和数据团队合作。
#### 资格要求
**必备条件**
- 软件工程和应用 AI 方面的经验。
- 在生产环境中参与生成式 AI 项目的实际经验。
- 高级英语水平。
**技术知识 i
查看英文原文
#### Company Description
Experian is a global data and technology company that powers opportunities for people and businesses around the world. We operate across a wide range of markets, including financial services, healthcare, automotive, agribusiness, insurance, among others. Experian invests in people and in advanced new technologies to unlock the power of data. We have an incredible team of 25,200 employees across 32 countries.
Our uniqueness is valuing yours. Experian’s people-centric, inclusive, and purpose-driven culture has been recognized with several awards — including World’s Best Workplaces™ 2025 (Fortune Global Top 25) and Great Place To Work™ in 26 countries, among others. Check out Experian Life on social media or explore our careers site to understand why. Experian is also proud to be an equal opportunity and affirmative action employer.
#### Job Description
We are looking for an **AI Engineer (GenAI Platform)** to work on the evolution of our global Generative Artificial Intelligence platform.
This position will play a fundamental role in the design, development, and operation of AI services that support engineering and product teams in various countries, enabling the creation of GenAI-based solutions that are scalable, secure, observable, and cost-efficient.
The focus of the role is the development of platform-level Generative AI capabilities, including agentic systems, model integration, LLMOps, and cost governance. This is not a position focused on training or fine-tuning models from scratch.
Key responsibilities
- Design and develop Generative AI services and multi-agent systems.
- Implement RAG (Retrieval-Augmented Generation), tool-calling, and agent orchestration solutions.
- Integrate and operate models via LLM gateways.
- Develop LLMOps practices for monitoring, observability, and governance.
- Implement consumption measurement, chargeback, and inference cost optimization mechanisms.
- Build and maintain data pipelines that support billing and metering processes.
- Apply MLOps, CI/CD, automated testing, and model lifecycle management practices.
- Handle incidents, monitoring, reliability, and continuous service improvement.
- Collaborate with global Product, Engineering, Platform, Security, and Data teams.
#### Qualifications
**Mandatory requirements**
- Experience in Software Engineering and Applied AI.
- Practical experience with GenAI projects in a production environment.
- Advanced English.
**Technical knowledge in:**
**GenAI and Agentic AI**
- Multi-agent orchestration
- Tool calling
- Multi-step reasoning
- RAG
- Prompt Engineering
- LangChain, LangGraph, or equivalent frameworks
**LLMOps and Platforms**
- LLM Gateways (LiteLLM or similar)
- Model integration via APIs
- Observability
- Evaluation of LLM-based applications
- Latency and performance optimization
- Vector databases and retrieval mechanisms
**Languages and Cloud**
- Advanced Python
- AWS (preferred)
- Best practices for architecture, observability, and reproducibility
**MLOps**
- Versioning and experiment tracking
- CI/CD
- Automated testing
- Deployment and rollback of AI services
**Data Engineering**
- Knowledge of data pipelines
- Batch and streaming
- Spark and Lakehouse architectures
- Data orchestration
**Preferred qualifications**
- Kafka and Event Streaming
- Terraform and Infrastructure as Code
- Databricks (Delta Lake and DLT)
- Experience with internal developer platforms
- Experience working in global and distributed environments
#### Additional Information
At Serasa Experian, we believe that diversity is essential for a healthier and more innovative work environment, where everyone can share experiences and express their ideas. That’s why we promote several initiatives to support inclusive recruitment and the professional development of our people.
We also have our affinity groups, created to empower and support individuals from underrepresented groups: ExperianPride (LGBTQIAPN+ community), Ubuntu (racial equity), Women in Experian (gender equity), Aspire (people with disabilities), and Connecting Generations (generations).
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