高级全栈产品工程师 - 乌克兰
Senior Full Stack Product Engineer - Ukraine
高级产品工程师
公司简介
ActiveProspect 的使命是让基于同意的营销成为在线客户获取的最佳渠道。我们为营销人员提供他们需要的产品，以大规模获取合格客户。我们的平台被数千家从事直客营销的公司所信赖，帮助他们节省浪费的开支，遵守不断变化的法规，并管理不断演变的合作伙伴环境。我们的旗舰产品 TrustedForm 每年用于认证超过 10 亿个数字客户注册，是 TCPA 合规性中记录事先明确书面同意的行业标准。
职位概述
你关注的是客户和业务成果，而不是工单。你像一个前移部署的工程师一样工作：你的根据地是一个核心团队，你进入问题所在的各种项目、计划和小组，跨整个技术栈（前端使用 React，AWS 上使用 Node.js 和 Python 服务）交付成果，然后将所学带回，使下一个团队更快前进。技术门槛很高，但编码能力只是基础，不是上限。这个角色的独特之处在于判断力：知道哪些是最值得发布的功能，何时要放弃自己的想法，以及何时 AI 输出足够好，何时需要手动干预。
你将在你的原生团队和你参与的项目之间来回切换，尽早交付，与客户沟通，并快速做出决策。
职责
- 全程负责你所部署的任何地方的成果。定义问题，设计它，交付它，负责相关指标。将方案简化到最经济有效的版本。在几天内进行原型开发。
- 紧密接触客户。跟踪销售和支持团队，参与顾问对话，并让客户现实驱动技术决策。提出要构建、推迟或取消的内容。
- 负责你所负责的领域并分享它。包括其接口、可靠性、性能和安全性，包括对其所负责系统的值班支持。同意和 PII 处理是客户信任的核心。将模式、工具和经验教训带回整个组织，而不是独自保留。
- 构建和扩展产品表面及底层平台。交付具有强大 UI/UX 视角的响应式、可访问的 React 界面，用 Node.js 和 Python 服务和 API 支持它们，并确保云批处理平台和数据管道在多租户产品扩展时保持可靠。
- 架构 AI 驱动的杠杆。构建 AI 辅助的工作流程，使其稳固，并随着工具的变化演进团队的实践（Cursor
查看英文原文
Senior Product Engineer
Company Overview
ActiveProspect is on a mission to make consent-based marketing the best channel for online customer acquisition. We provide marketers the products they need to acquire qualified customers at scale. Our platform is trusted by thousands of companies engaged in direct-to-consumer marketing, helping them save wasted spend, comply with ever-changing regulations, and manage a constantly evolving partner landscape. Our flagship product, TrustedForm, is used to certify over 1 billion opt-in digital customer leads every year and is the gold standard for documenting prior express written consent for TCPA compliance.
Job Summary
You own customer and business outcomes, not tickets. You work like a forward-deployed engineer: your home base is a core team, and you deploy into projects, initiatives, and pods where the problem is, ship the outcome across the full stack (React on the frontend, Node.js and Python services on AWS), then carry what you learned back so the next team moves faster.. The technical bar is high, but coding ability is the floor here, not the ceiling. What sets this role apart is judgment: knowing the smallest thing worth shipping, when to kill your own idea, and when AI output is good enough versus when to override it.
You'll move between your home team and the initiatives you deploy into, shipping early, talking to customers, and deciding fast.
Responsibilities
- Own outcomes end-to-end, wherever you're deployed. Frame the problem, design it, ship it, own the metric. Descope to the cheapest version that works. Prototype in days.
- Stay close to customers. Shadow sales and support, join advisory conversations, and let customer reality drive technical decisions. Propose what to build, defer, and kill.
- Own your domain and share it. Its interfaces, reliability, performance, and security, including on-call for the systems you own. Consent and PII handling are central to customer trust. Bring patterns, tooling, and hard-won context back to the wider org rather than hoarding them.
- Build and scale both the product surface and the platform beneath it. Ship responsive, accessible React interfaces with a strong UI/UX eye, back them with Node.js and Python services and APIs, and keep the cloud batch platform and data pipelines that deliver multi-tenant products reliable as they scale.
- Architect AI-driven leverage. Build AI-assisted workflows that hold up, evolve the team's practices as tooling changes (Cursor, Claude Code, and whatever comes next), and look for product wins AI unlocks (smarter routing, anomaly detection, and more).
- Multiply the teams you touch. Mentor on judgment and product sense, not just syntax. Write decision memos and ADRs. Enable Product and Design to self-serve.
Qualifications and Skills
- A track record of shipping something end-to-end that you cared about and owning the outcome, not just the code.
- Product judgment: pushing back on a bad spec, proposing the cheapest experiment, descoping well, and collaborating with Product to suggest solutions rather than waiting for a fully specced ticket.
- Comfort embedding with unfamiliar teams and codebases, getting productive fast, and leaving them better than you found them.
- Deep full-stack expertise: React (component lifecycle, state management, rendering optimization), JavaScript/TypeScript, and modern CSS on the frontend; Node.js and Python services, RESTful APIs, and asynchronous data handling on the backend.
- Cloud and data-pipeline depth: AWS core services (Lambda, EC2, S3, DynamoDB, API Gateway) and cloud batch / workflow orchestration (Step Functions, Airflow, or similar) to deliver multi-tenant batch products and data solutions reliably at scale.
- A strong UI/UX eye: you turn wireframes, mockups, and ambiguous requirements into intuitive, accessible, user-centric journeys.
- Strong systems design judgment in ambiguous contexts, and a security mindset aligned with sensitive consumer data and compliance.
- Fluency building your own AI-assisted workflows and reading AI output critically. Daily use of AI-native tools (Cursor, Claude Code) and precise prompting across OpenAI and Claude models, with the judgment to know when to trust output, how to review it for hidden bugs and security issues, and when to override it.
- Clear written and verbal communication. Mentorship experience. 5-10% travel.
How It Works
You'll report to an Engineering Manager who owns several teams and stays out of their daily flow. As you embed, you'll often act as the player-coach Tech Lead, owning technical direction while the EM owns delivery health and stakeholder alignment across the group.
Success looks like movement in a user or business metric you/your team owns, high-value work deliberately not built, decisions made fast, and teams that move faster after you've worked with them, not just while you're there.
Reports To
Engineering Manager
Originally posted on Himalayas