AI Python 后端工程师 — 前沿部署
AI Python Backend Engineer — Forward Deployed
🚀 加入我们的远程数据产品与机器学习初创公司！ 🚀
在 Muttdata，我们构建创新的数据产品和机器学习解决方案，帮助公司解决复杂的业务挑战。作为一家快速发展的远程优先初创公司，我们对技术、协作和持续学习充满热情。
我们正在寻找一位积极主动、技术能力强的 AI 后端工程师（Python）——向前部署，加入我们的团队 🐶🚀。你将参与我们一家银行客户的战略项目，嵌入到银行的 AI 平台团队中，将基于大语言模型的代理系统部署到银行的各个业务单元。
这是一个嵌入式角色：你将加入一个有代理需要构建或部署的团队，在平台的框架（LangGraph、LiteLLM、Langfuse）上构建它，通过银行的控制流程将其投入生产，并让该团队能够独立运营。一旦该代理上线，你将前往下一个团队。你在每个轮岗中学到的内容会反馈到平台中，用于改进模板、可观测性和部署流程。
这个职位需要强大的主人翁意识、扎实的架构判断力，以及构建安全、高效且可扩展系统的能。你将在快节奏、高标准的环境中与跨职能团队紧密合作，这在金融行业是常态。
🚀 我们所做的
- 利用我们的专业知识，我们为需求规划和预算预测构建现代机器学习系统。
- 开发可扩展的数据基础设施，我们提升高层决策，根据每个客户的需求进行定制。
- 提供全面的数据工程和定制 AI 解决方案，我们优化基于云的系统。
- 使用生成式 AI，我们帮助电商平和零售商更快地创建高质量的广告。
- 构建深度学习模型，我们提升视觉识别和自动化，适用于多个行业，提高产品分类、质量控制和信息检索。
- 开发推荐模型，我们在电商、流媒体和数字平台上个性化用户体验，提升参与度和转化率。
🌟 我们的合作伙伴
- 亚马逊网络服务
- Astronomer
- Databricks
🌟 我们的价值观
- 📊 我们是数据极客
- 🤗 我们是开放的团队合作者
- 🚀 我们承担责任
- 🌟 我们拥有积极的心态
🔍 对我们正在做什么感到好奇吗？查看我们的案例研究，并深入阅读我们的博客文章，了解更多关于我们的文化和我们正在进行的令人兴奋的项目！ 🚀
查看英文原文
🚀 Join Our Remote Data Products & Machine Learning Startup! 🚀
At Muttdata, we build innovative Data Products and Machine Learning solutions that help companies solve complex business challenges. As a fast-growing, remote-first startup, we're passionate about technology, collaboration, and continuous learning.
We're looking for a proactive, technically strong AI Backend Engineer (Python) — Forward Deployed to join our team 🐶🚀. You'll work on a strategic project for one of our banking clients, embedded within the bank's AI platform team, taking LLM-based agents into production across the bank's business units.
This is an embedded role: you join a team that has an agent to build or deploy, build it on top of the platform's scaffolding (LangGraph, LiteLLM, Langfuse), take it to production through the bank's controls, and leave the team able to operate it on their own. Once that agent is live, you move on to the next team. What you learn in each rotation feeds back into the platform as improvements to the template, observability, and deployment process.
This role requires strong ownership, solid architectural judgment, and the ability to build systems that are secure, performant, and built to scale. You'll collaborate closely with cross-functional teams in a fast-paced, high-standards environment typical of the financial industry.
🚀 What We Do
- Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
- Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
- Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
- Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
- Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
- Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.
🌟 Our Partnerships
- Amazon Web Services
- Astronomer
- Databricks
🌟 Our Values
- 📊 We are Data Nerds
- 🤗 We are Open Team Players
- 🚀 We Take Ownership
- 🌟 We Have a Positive Mindset
🔍 Curious about what we’re up to? Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects we’re working on! 🚀
Responsibilities 🤓
- Build agents on top of the platform's scaffolding, including tool calling, integration with the bank's internal APIs, state and conversation management, and guardrails.
- Take each agent to production on AWS: containers, CI/CD, secrets, permissions, networking, and the bank's security controls.
- Define and run evals before going to production, and monitor with Langfuse once deployed (quality, latency, cost).
- Unblock technical and process issues together with the Identity, Security, DevSecOps, and Networking teams.
- Leave documentation and runbooks so the team can operate the agent independently, transferring knowledge before rotating to the next team.
- Feed what you learn in each rotation back into the platform: improvements to the agent template, the deployment pipeline, and observability.
Required Skills 💻
- At least one LLM-based agent or system taken to production and operated, using LangGraph or an equivalent framework.
- 4+ years of backend experience in Python, with production services (FastAPI or another async framework).
- Ability to independently take a service from the repo to production on AWS: containers, CI/CD, and observability.
- Experience with LLM evaluation (evals, tracing, hallucination control) and agent observability (Langfuse or similar).
- Daily use of AI development tools (GitHub Copilot, Claude Code, Cursor).
- Ability to join a new team, quickly understand its context, and unblock issues with both technical and business stakeholders.
- Clear communication and a habit of documenting and handing off what you build.
Nice to have 💻
- Experience in banking or fintech.
- Kubernetes and Terraform.
- API security (OAuth2/JWT).
- RAG and vector databases.
- Building your own MCP servers.
- Spec-Driven Development.
- Prior experience as an embedded client consultant or in a forward-deployed role.
🎁 Perks
- 🌍 Remote-first culture – work from anywhere!
- 🚀 In-Company English Lessons.
- 💪 Wellhub or sports club stipend to stay active
- 🚀 AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
- 🍕 Food credits via Pedidos Ya – because great work deserves great food.
- 🎂 Birthday off + an extra vacation week (Mutt Week! 🏖️)
- 🤝 Referral bonuses – help us grow the team & get rewarded!
- ✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!
- 👶 Monthly Childcare Reimbursement – Because supporting families matters too