首席Python工程师（代理AI）
Principal Python Engineer for Agentic AI
哪些挑战在等待你
- 你将主导我们基于 LLM 的代理应用（如聊天机器人）的 Python 后端开发与优化，以及我们 Agentic AI 平台的持续演进
- 你将为 Agentic AI 工程师团队提供技术方向，定义工程标准，评审架构决策，并支持团队交付可扩展、可靠且生产就绪的解决方案
- 你将通过稳定和优化现有解决方案来提升客户体验，包括更好的可视化、自动化验证、函数调用、代理操作、可观测性以及质量保障
- 你将识别并实现新的业务需求，并将其转化为可持续的技术解决方案
- 你将与业务部门合作，积极参与客户研讨会、会议和电话沟通。能够清晰地向业务同事解释技术话题，并展现出顾问思维是必不可少的
- 你将主导技术头脑风暴会议、架构讨论、代码审查和配对编程
- 你将识别自动化、Agentic AI 和数据科学的潜在应用场景。欢迎创新想法
- 你将积极指导工程师，支持他们的成长，并在团队中推广软件工程最佳实践
你的技能
- 至少8年使用 Python 构建和运维生产级软件的经验，优选使用 FastAPI、Pydantic、Temporal 等框架及相关技术
- 有带领工程师、技术工作流或软件开发团队的实战经验
- 对软件架构、分布式系统、API 设计、异步处理、可扩展性、弹性及生产运维有深刻理解
- 熟悉 LLM 和 Agentic AI 框架，如 LangChain、LangGraph、LlamaIndex，以及 Azure OpenAI 和 OpenAI API。理想情况下，你已使用这些技术构建并运维过生产就绪的解决方案
- 具有关系型数据库（如 PostgreSQL）、内存数据库（如 Redis）以及文档或搜索数据库（如 Elasticsearch 和 MongoDB）的实际经验
- 有设计、构建和运维生产环境 RESTful API 和 Web 服务应用的实战经验
- 有云和 DevOps 经验，包括 Docker、CI/CD 工具（如 GitHub Actions 或 GitLab CI），以及在 Azure、AWS 上的部署经验
查看英文原文
Which challenges are expecting you
- You will lead the development and improvement of our Python backends for LLM-backed agent applications, such as chatbots, as well as the ongoing evolution of our Agentic AI platform.
- You will provide technical direction for a team of Agentic AI engineers, define engineering standards, review architectural decisions, and support the team in delivering scalable, reliable, and production-ready solutions.
- You will improve customer experience by stabilizing and enhancing existing solutions, including better visualization, automated validations, function calling, agent actions, observability, and quality assurance.
- You will identify and implement new business requirements and translate them into sustainable technical solutions.
- You will drive cooperation with the business and actively contribute to customer workshops, meetings, and calls. The ability to explain technical topics clearly to business colleagues and demonstrate a consultant’s mindset is essential.
- You will lead technical brainstorming sessions, architecture discussions, code reviews, and pair programming sessions.
- You will identify potential use cases for automation, Agentic AI, and data science. Innovative ideas are welcome.
- You will actively mentor engineers, support their development, and promote software engineering best practices across the team.
Your skills
- At least 8 years of experience building and operating production-grade software in Python, preferably using frameworks such as FastAPI, Pydantic, Temporal, and similar technologies.
- Proven experience leading engineers, technical workstreams, or software development teams.
- Strong understanding of software architecture, distributed systems, API design, asynchronous processing, scalability, resilience, and production operations.
- Preferably strong knowledge of LLM and Agentic AI frameworks such as LangChain, LangGraph, LlamaIndex, as well as Azure OpenAI and OpenAI APIs. Ideally, you have already built and operated a production-ready solution using these technologies.
- Practical experience with relational databases such as PostgreSQL, in-memory databases such as Redis, and document or search databases such as Elasticsearch and MongoDB.
- Proven experience designing, building, and operating RESTful APIs and web service applications in production.
- Cloud and DevOps experience, including Docker, CI/CD tools such as GitHub Actions or GitLab CI, and deployment to Azure, AWS, or GCP.
- Understanding of production requirements for Agentic AI systems, including testing, evaluation, observability, security, cost management, and reliability.
- You are comfortable making technical decisions, explaining trade-offs, and aligning engineers and stakeholders around a clear solution.
- You are flexible, comfortable with changing priorities, and prefer working in agile environments such as XP, Scrum, or Lean.
- You can explain complex architectures and technologies in a clear and accessible way to customers and business stakeholders.
- You actively mentor more junior personnel and share your knowledge of software development lifecycle and best practices.
- Fluent written and spoken English.
Nice to have
- German language skills.
- Prompt engineering and LLM evaluation experience.
- Familiarity with MLOps or AI workflow orchestration tools such as MLflow or Dagster.
- Experience with Kubernetes, infrastructure as code, or LLM observability tools.
- Domain-specific experience in telecommunications or finance.
Deutsche Telekom Services Europe (DTSE) was founded by Deutsche Telekom AG and delivers support services, with focus on HR, for the European footprint of DT Group.
Join us in this international environment and you’ll be exposed to many different competencies, cultures and languages.
If you want to join this innovative team and take the opportunity to be part of a growing company, apply now!
DTSE-RO is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. All employment decision at DTSE-RO are based on business needs, job requirements and individual qualifications, with no regard to race, color, religion or belief, national, social or ethnic origin, sex, age, physical, mental or sensory disability, sexual orientation and gender identity.
DTSE-RO will not tolerate discrimination or harassment based on any of these characteristics.
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Originally posted on Himalayas