技术产品负责人 | 生成式AI交付（中级）
Technical Product Owner | GenAI Delivery (Mid-level)
Provectus 是一家高级 AWS 合作伙伴和 Anthropic 合作伙伴，被列为 Forrester 的 AI 技术服务全景图。我们大约有 420 名工程师，为金融、医疗健康与生命科学、零售和娱乐行业的企业客户构建生产级 AI。我们基于真实客户的数据构建定制系统，而不是现成的产品或演示。
我们在哥伦比亚和哥斯达黎加的交付团队中正在招聘一名解决方案负责人。这是一个早期职业岗位，但不是培训岗位。你将位于客户和工程团队之间，负责一部分工作范围，并需要自己判断下一步该怎么做。
我们寻找的候选人具有特定背景：你最初是技术出身，作为软件、数据或机器学习工程师，已经转向产品业务方面，或者现在准备做出这样的转变。你是团队中第一个用 AI 工具自动化自己工作的那个人。
你将负责：
- 负责客户项目的一个明确部分，从用例定义到待办事项、发布和结果
- 与客户利益相关者进行发现会议和研讨会，并将听到的内容转化为工程师可以构建的书面范围
- 将技术限制转化为业务语言，将业务目标转化为技术需求
- 维护一个经过整理的待办事项列表，包含大小明确、技术具体的用户故事，并推动冲刺计划和发布节奏
- 使用我们的交付工具栈（包括 Claude、Claude Code、MCP 服务器和 Skills）在真实客户数据上快速原型开发
- 与 GenAI 和代理 AI 构建紧密合作，包括 RAG、代理工作流和 LLM 集成，足以判断质量并解释权衡
- 为你的工作范围定义成功指标，并诚实地报告进展，包括当某些事情不奏效时
- 构建可重复使用的工件、演示和文档，使下一个项目比你的项目启动得更快
- 与美国和拉美地区的首席架构师、前线部署工程师和客户团队合作
你将带来：
- 2 至 4 年的总专业经验，包括作为软件、数据或机器学习工程师的实际工程经验
- 至少 1 年的产品、交付或面向客户的角色经验，如产品负责人、技术产品负责人、业务分析师、交付负责人或同等职位
- 日常使用 GenAI 工具在自己的工作中，优先使用 Claude 和 Claude Code，并有具体的工作流程示例
查看英文原文
Provectus is a Premier AWS Partner and an Anthropic partner, featured in Forrester's AI Technical Services Landscape. We are roughly 420 engineers building production AI for enterprise clients in Financial Services, Healthcare and Life Sciences, Retail, and Entertainment. We build custom systems on live client data, not off the shelf products and not demos.
We are opening a Solution Owner seat on our Delivery team in Colombia and Costa Rica. This is an early career seat, but it is not a training seat. You will sit between the client and the engineering team on a real engagement, own a slice of scope, and be expected to figure out the next step yourself.
The profile we are looking for is specific: you started technical, as a software, data, or ML engineer, and you have already moved toward the business side of building products, or you are ready to make that move now. You are the person on the team who automates their own work with AI tools before anyone asks.
What You Will Do:
- Own a defined slice of a client engagement, from use case framing through backlog, release, and result
- Run discovery sessions and workshops with client stakeholders, and turn what you hear into written scope engineers can build against
- Translate technical constraints into business language, and business goals into technical requirements
- Maintain a groomed backlog with sized, technically specific stories, and drive sprint planning and release cadence
- Prototype rapidly on live client data using our delivery stack, including Claude, Claude Code, MCP servers, and Skills
- Work alongside GenAI and agentic AI builds, including RAG, agent workflows, and LLM integrations, closely enough to judge quality and explain trade offs
- Define success metrics for your slice of scope and report progress honestly, including when something is not working
- Build reusable artifacts, demos, and documentation so the next engagement starts faster than yours did
- Partner with Principal Architects, Forward Deployed Engineers, and account teams across US and LATAM time zones
What You Will Bring:
- 2 to 4 years of total professional experience, including hands on engineering time as a software, data, or ML engineer
- At least 1 year in a product, delivery, or client facing role such as Product Owner, Technical Product Owner, Business Analyst, Delivery Lead, or equivalent
- Daily use of GenAI tools in your own workflow, Claude and Claude Code preferred, with concrete examples of workflows you redesigned
- Ability to read code and technical documentation well enough to hold a real conversation with senior engineers
- Practical Agile and Scrum experience: backlog, sprints, planning, retrospectives
- Written and spoken English at B2 or above, comfortable leading a client call without a manager in the room
- Self direction as a default. You are given a goal and ambiguity, not a task list, and you move anyway
- Based in Colombia or Costa Rica
Nice to Have:
- Exposure to Financial Services and Insurance or Healthcare and Life Sciences clients
- Working understanding of GenAI concepts: prompt engineering, RAG, embeddings, vector databases, agentic patterns
- Familiarity with AWS, especially Bedrock, SageMaker, Lambda, or S3
- Experience shipping an LLM or RAG feature that reached real users
- Experience building your own automations, scripts, MCP integrations, or internal tools
- Consulting or professional services background
- Certifications such as CSPO, SAFe PO/PM, or AWS Cloud Practitioner
What We Offer:
- Real client delivery on frontier AI from month one, not shadowing
- Direct access to Principal Architects and Forward Deployed Engineers as your working peers
- Anthropic and AWS partnership work, with early access to tooling and premium AI subscriptions
- Internal training programs and full support for AWS and Claude certifications
- A clear growth path toward Senior Solution Owner or Solutions Architecture
- Remote work with flexible hours across US and LATAM overlap
- Long term B2B collaboration
- Equipment budget and all the tooling you need