Original listing text, shown exactly as published by the company.
What You’ll Do
1. Product Discovery & Problem Framing
- Own a clearly defined problem area within the platform.
- Conduct lightweight discovery: customer calls, support ticket mining, analytics review, win/loss insights, session replays.
- Write sharp problem statements and define measurable success criteria.
- Turn ambiguity into structured thinking and validated hypotheses.
- Identify opportunities to improve activation, retention, revenue, or operational efficiency.
2. Requirements & Product Documentation
- Define MVP vs V1 vs V2 iterations and define the requirement
- Goals & KPIs
- In-scope / out-of-scope
- User stories & acceptance criteria
- Edge cases & risks
- Maintain clear decision logs and documentation.
- Prevent scope creep through structured thinking.
3. UX & Experience Ownership
- Design intuitive user flows and information architecture.
- Think deeply about onboarding, empty states, failure states, and microcopy.
- Ensure experiences align with platform conventions.
- Ship functional, usable interfaces even when design support is limited.
- Advocate for customer clarity and simplicity.
4. Full Stack Architecture & Engineering Execution
- Architect scalable systems across frontend, backend, APIs, automation, and AI workflows.
- Ship production-grade code with high reliability and maintainability.
- Balance latency, performance, scalability, and cost.
- Build integrations and automation frameworks.
- Own migrations, backward compatibility, and system resilience.
5. AI-Native System Design
- Build LLM-powered features, agents, or workflow automation.
- Design evaluation loops and guardrails.
- Optimize inference cost, latency, and reliability.
- Continuously iterate based on real usage signals.
6. Analytics, Instrumentation & Experimentation
- Define KPIs for every feature shipped.
- Instrument events, funnels, and telemetry.
- Monitor adoption, activation, engagement, and failure metrics.
- Run lightweight experiments or A/B tests.
- Use data to drive iteration and continuous improvement.
7. Operational Excellence
- Improve system observability and monitoring.
- Automate internal workflows to reduce cycle time.
- Maintain clean documentation and runbooks.
- Continuously reduce tech debt and UX debt.
What Success Looks Like
- Reduced cycle time from idea → production.
- Production-grade systems (not prototypes).
- Measurable improvement in product KPIs.
- Lower support tickets and improved customer satisfaction.
- Clear documentation and scalable architecture.
- Strong ownership and minimal oversight required.
Minimum Qualifications
- 5+ years of experience as a Product Manager
- Demonstrated track record of shipping production systems
- Strong systems thinking and logical reasoning
- High ownership mindset; operates well with minimal supervision
- Comfortable with ambiguity and fast iteration cycles
- Experience with APIs, automation tools, or AI platforms
- Ability to reason about infrastructure tradeoffs and system reliability
Preferred Qualifications
- Experience building LLM-based or AI-driven products
- Familiarity with evaluation frameworks, monitoring, or instrumentation
- Experience with data pipelines, analytics, or telemetry
- Strong UX and front-end sensibility
- Portfolio or GitHub showcasing deployed systems
- Stack: React / Vue / Angular · Node.js / Python / Java
Core Technical Skills
- Frontend frameworks (React, Vue, Angular, etc.)
- Backend development (Node.js, Python, Java, etc.)
- API design and system integration
- Database architecture & optimization
- Cloud infrastructure fundamentals
- Monitoring and observability tools
- Performance optimization
Core Product Management Skills
- Product discovery & customer research
- Problem framing & structured thinking
- Roadmapping & prioritization frameworks
- KPI definition & data-driven iteration
- UX thinking & experience design
- Stakeholder communication & alignment
- Outcome-based ownership mindset
Who This Role Is For
- Builders who prefer ownership over hierarchy and want to own outcomes end-to-end.
- Engineers who think like product leaders and make strong product decisions.
- Product thinkers who can ship real, production-grade systems, not just write specs.
- Individuals comfortable operating in high-ambiguity environments with minimal process.
- Builders who actively leverage AI tools, automation, and modern development workflows to accelerate prototyping, coding, testing, and product development.
- Individuals who use AI-assisted development (LLMs, copilots, automation workflows, code generation tools, etc.) to move faster while maintaining high engineering quality.
- People excited about moving quickly from idea → prototype → production, using AI and automation to dramatically reduce development cycles.
