AI-First Product Manager (Ops Transformation)
关于 Compato AI 我们正在通过人工智能驱动的自动化转型债务收取行业，以提供符合要求，同情感和收入驱动的客户体验。我们的使命是帮助机构，贷款人和金融机构重新想象收集，并将人类水平对话与人工智能的效率结合起来。我们是一个快速增长的金融科技初创公司，构建了现代收藏的运营骨干，无论是进来，出发或数字自我服务。如果你通过消除混乱的手工流程并重建它们为人工智能原生工作流程而获得活力，并且如果你可以把操作疼痛转换成固定的自动化，那么这个角色可能适合你。你将如何在这个角色中产生影响 我们正在寻找我们的第一个人工智能第一产品经理 （运营转型）,一个构建者，谁融合了系统级人工智能思维的产品管理严格。你的任务：把我们收债经理的游戏书，剥离它到头条，并重新设计为 AI 原生组织。这意味着沉浸于日常运营，识别合规重瓶，重新思考它们应该如何工作在一个人工智能的世界。你将拥有从原始操作员痛苦 →原型自动化 →采用和扩展的旅程。这是一个同样舒适的人员的角色，负责监视前线工作人员，起草 RICE+风险分数自动化优先事项，并指导 MVP 工程构建 （或在 Cursor/Claude 代码中进行原型制作）.简而言之：你将模糊性转换为工作自动化和可重复的游戏书籍，这些内容将跨部门汇集价值。责任发现和翻译 · 沉浸于日常收集操作中来绘制 SOP 和表面疼痛点。·应用就业完成和人类学方法来重新框架运营商需求。·通过排名，影响，合规风险等确定和订购自动化机会 （RICE +风险层次）设计和执行。· 提起规格，或者自己做原型或管理轻量级工程构建。· 快速完成废弃的 MVP;测量周期时间，合规性和吞吐量。· 在可共享的帖子，SOP 和 AI-First Ops 手册中捕获学习，因此获得复合效果。治理与遵守。· 应用严格的防护：T0T3风险层次，人在循环中的需求。·定义自动化治理工具 （SLAs,SOPs,审计日志）. ·确保人工智能工作流程可以解释，可进行审核和符合。影响和扩展 ·跟踪采用：从 AI 开始的任务% . · 衡量业务运营。
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About Kompato AI
We’re transforming the debt collection industry with AI-powered automation that delivers compliant, empathetic, and revenue-driving customer experiences. Our mission is to help agencies, lenders, and financial institutions reimagine collections by blending human-level conversation with the efficiency of AI. We’re a fast-growing fintech startup building the operating backbone for modern collections—whether inbound, outbound, or digital self-service.
If you’re energized by stripping down messy, manual processes and rebuilding them as AI-native workflows, and if you can translate operational pain into automation that sticks, this role might be for you.
How you will make an impact in this role
We are looking for our first AI-First Product Manager (Ops Transformation) — a builder who fuses product management rigor with systems-level AI thinking.
Your mandate: take our debt collection operator’s playbook, strip it to the studs, and redesign it for an AI-native organization. That means immersing yourself in daily ops, identifying compliance-heavy bottlenecks, and rethinking how they should work in an AI-first world. You’ll own the journey from raw operator pain → prototype automation → adoption and scaling.
This is a role for someone equally comfortable shadowing frontline staff, drafting RICE + risk-scored automation priorities, and guiding MVP engineering builds (or prototyping in Cursor/Claude code yourself). In short: you’ll turn ambiguity into working automations and repeatable playbooks that compound value across departments.
Responsibilities
Discovery & Translation
- Immerse in daily collections ops to map SOPs and surface pain points.
- Apply Jobs-to-Be-Done and anthropological methods to reframe operator needs.
- Identify and rank-order automation opportunities by reach, impact, compliance risk, and more (RICE + risk-tier).
Design & Execution
- Draft specs and either prototype yourself or manage lightweight engineering builds.
- Ship scrappy MVPs quickly; measure cycle-time, compliance adherence, and throughput.
- Capture learnings in shareable posts, SOPs, and the AI-First Ops Handbook so wins compound.
Governance & Compliance
- Apply strict guardrails: T0–T3 risk tiers, human-in-the-loop where required.
- Define automation governance artifacts (SLAs, SOPs, audit logs).
- Ensure AI workflows are explainable, auditable, and compliant.
Impact & Scaling
- Track adoption: % of ops tasks starting with AI.
- Measure business outcomes: revenue impact, FTE leverage, error reduction.
- Industrialize successful prototypes into repeatable modules.
Requirements
Must have
- 5+ years in product management, ops transformation, or program management.
- Proven track record of translating manual SOPs into automated, governed workflows.
- Experience working in or adjacent to regulated industries (fintech, healthcare, collections, gov).
- Familiarity with automation stacks (RPA, workflow orchestration, APIs) and emerging AI architectures (LLMs, agentic systems).
- Data self-service skills (SQL, dashboards) a plus.
- Startup-tested: you can bring order without needing layers of process to get going.
Preferred
- Start with AI: treat automation as the reflexive first step in ops design.
- Human as router: know when to elevate to judgment, compliance, or context.
- Compound wins: document and share so no automation stays siloed.
- Culture builder: normalize AI-first rituals (e.g., “AI Win of the Week”) to drive adoption.
- Execution-first: You thrive in ambiguity, move from pain points to working solutions fast.
- AI-native reflexes: You know LLMs, RAG, embeddings, and agentic orchestration — not just in theory but in how they reshape real workflows.
- Systems thinker: You can zoom out to see the process end-to-end and zoom in to fix the brittle step that breaks it.
- Operator empath: You can shadow a frontline operator and feel where the friction lives.
- Scrappy builder: Bonus if you can prototype in Cursor IDE/Claude code or SQL; at minimum, you’re fluent enough with code to direct engineers effectively.
- Compliance aware: You respect the red lines — automation never compromises legal, regulatory, or reputational guardrails.
At Trusting Social, we live by ownership, integrity, and agility in execution. We believe in doing what's right, what's best, and what's innovative. If you're smart, driven, and want to make a difference in the world with the most advanced and fascinating technology, we invite you to be part of our rockstar team!
For more information about us, please visit our website:
Originally posted on Himalayas