高级解决方案架构师 | Python和生成式AI
Senior Solutions Architect | Python and GenAI
Provectus 是一家专注于 AI/ML 解决方案的咨询与专业服务公司。Provectus 是 AWS 首席合作伙伴和 Anthropic 合作伙伴，帮助企业客户从 AI 实验过渡到 AI 在生产环境中运行。
我们正在改变交付方式。不再将设计交给客户并等待他人构建，我们的工程师直接嵌入客户团队，自己交付系统。我们称之为 Forward Deployed 交付模式。在设计任何东西之前，你会花时间与那些要被系统改变工作的人相处，因此架构反映的是实际的工作方式，而不是需求文档中描述的方式。
我们正在寻找一位拥有深厚 Python 和生成式 AI 经验的高级软件工程师或解决方案架构师，希望以这种方式工作：深入代码、贴近客户，并直接对系统是否被使用负责。直接与客户沟通是这个职位的核心。有前期销售经验者优先。
你将负责：
- 在整个项目周期内嵌入客户团队，而非远程协作
- 在设计任何东西之前，与那些要被系统改变工作的人相处，使架构建立在实际工作方式的基础上
- 编写高质量的 Python 代码，涵盖 AI 集成、后端服务和 RESTful API（Flask、Django 或 FastAPI）
- 设计、构建和优化 RAG 系统和代理式 AI 解决方案，这些系统在生产环境中运行，而非演示或笔记本
- 在项目周期内负责系统设计和架构决策：微服务 vs 单体架构，同步 vs 事件驱动，SQL vs NoSQL
- 从发现阶段到交付阶段，主导项目的整体技术方向
- 作为客户的直接技术联系人：展示架构，为权衡做出辩护，并在范围与时间表或预算不符时进行抵制
- 在相关情况下支持售前活动，包括发现通话、技术方案、范围定义和面向客户的演示
- 主持架构评审，撰写技术设计文档，并为整个 Python 实践制定标准
- 将所学知识反馈到 Provectus 的蓝图库中，使下一次项目能更高效地启动
- 指导工程师，领导代码审查，并在团队中分享知识
你将带来：
- 7 年以上构建和运行生产环境的经验
查看英文原文
Provectus is a consulting and professional services firm with a focus on AI/ML based solutions. Provectus is an AWS Premier Partner and an Anthropic partner, helping enterprise clients move from AI experimentation to AI running in production.
We are changing how we deliver. Instead of handing a client a design and waiting for someone else to build it, our engineers embed directly inside the client's team and ship the system themselves. We call this Forward Deployed delivery. Before you design anything, you spend real time with the people who do the work the system is meant to change, so the architecture reflects how the work actually happens, not how a requirements document described it.
We are looking for a Senior Software Engineer or Solutions Architect with deep Python and Generative AI experience who wants to work this way: deep in the code, close to the client, and directly accountable for whether the system gets used. Direct client communication sits at the center of this role. Prior presales experience is a strong plus.
What You Will Do:
- Embed with the client team for the length of the engagement, working inside their environment rather than alongside it from a distance
- Spend time with the people who do the job the system is meant to change before you design anything, so the architecture is grounded in how the work actually happens
- Write clean, production grade Python across AI integrations, backend services, and RESTful APIs (Flask, Django, or FastAPI)
- Design, build, and optimize RAG systems and agentic AI solutions running in production, not demos or notebooks
- Own system design and architectural decisions across the engagement: microservices vs monolith, sync vs event driven, SQL vs NoSQL
- Own the technical direction of the engagement from discovery through delivery
- Act as the client's direct technical point of contact: present architecture, defend trade offs, and push back on scope when it does not match timeline or budget
- Support presales activities where relevant, including discovery calls, technical proposals, scoping, and client facing demos
- Lead architecture reviews, produce technical design documents, and contribute to standards across the Python practice
- Feed what you learn back into Provectus's blueprint library, so the next engagement starts further ahead
- Mentor engineers, lead code reviews, and share knowledge across the team
What You Will Bring:
- 7+ years building and running production systems; hands on production experience is required, demo only or POC only backgrounds will not be considered
- Production experience with RAG systems and LLM based agentic workflows that are live and running, not prototypes
- Backend development experience with Flask, Django REST, or FastAPI
- Recent, hands on experience with AWS (SageMaker, Bedrock, Lambda, ECS, S3, SQS, ECR, or similar); GCP considered
- Experience with LLM APIs (OpenAI, Anthropic Claude, or AWS Bedrock)
- Strong Python proficiency: OOP, design patterns, clean architecture, and performance optimization
- Demonstrated experience making and defending system design and architectural trade off decisions
- Comfortable owning direct communication with client stakeholders, without a project manager relaying the conversation
- Genuine willingness to spend time close to the people who do the job before you design a system to change it, and comfort with an engagement that starts underspecified by design
- Strong testing practices: pytest, mocking, and integration tests for AI systems
- Experience with Docker and Kubernetes
- Understanding of LLM evaluation techniques and quality assurance approaches
- Experience deploying and maintaining AI/ML models in production environments
- Already using AI assisted development tools in your daily workflow (Claude Code, Copilot, or similar)
- Proactive and self directed; you own outcomes end to end and spot problems before they are handed to you
- B2+ English, comfortable collaborating across distributed, multicultural teams
Nice to Have:
- Exposure to Financial Services or Healthcare and Life Sciences, our two primary practice verticals
- Presales experience: cost estimation, cloud architecture cost optimization, scoped and phased delivery plans
- Prior consulting, professional services, or other embedded client facing delivery
- Experience with React or Vue
- AWS or Claude Code certifications
- Experience with Streamlit or Gradio for AI prototyping
- Modern Python tooling (ruff, uv, pyproject.toml, pyright)
- CI/CD pipeline experience (GitHub Actions, GitLab CI)
- Experience in an additional language (Go, Node.js, or Rust)
What We Offer:
- Remote-friendly culture
- Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance
- Career growth; we actively develop our engineers
- Access to the latest AI tools and premium subscriptions
- Long-term B2B collaboration
- Private medical insurance or a budget for your medical needs
- Paid sick leave, vacation, and public holidays
- Equipment and all the tech you need for comfortable, productive work