What You’ll Do
- Product Strategy & Roadmap: Own the end-to-end product lifecycle, from initial market research and vision setting to execution and post-launch optimization.
- Requirement Engineering: Author detailed Product Requirement Documents (PRDs) and User Stories that account for complex business logic, edge cases, and high-quality user flows.
- AI Feature Integration: Identify opportunities to embed AI (e.g., LLMs, automation, predictive analytics) into the product to solve user pain points and enhance value.
- Cross-functional Leadership: Act as the primary liaison between stakeholders, design, and engineering teams to ensure alignment on project scope and delivery timelines.
- Data-Driven Decision Making: Define key performance indicators (KPIs) and utilize data analytics to track product health and inform future feature iterations.
- Quality Assurance Partnership: Collaborate with the QA team to establish clear acceptance criteria and ensure the final output meets rigorous stability and performance standards.
Requirements
- Experience: 10+ years of experience in Software Product Management, successfully managing products through multiple release cycles.
- SaaS & Cloud Familiarity: Proven experience in building or managing SaaS (Software as a Service) applications and a strong understanding of Cloud Services (e.g., AWS, Ali Yun) from a product perspective.
- Methodology: Strong understanding of the Software Development Lifecycle (SDLC) and experience working within Agile/Scrum environments.
- AI Literacy: A solid conceptual understanding of Artificial Intelligence capabilities (especially Generative AI) and the ability to translate AI potential into practical product features.
- Logical Prowess: Exceptional analytical and logical thinking skills, with a proven ability to map out complex systems and handle intricate "if-then" scenarios.
- Communication: Mastery in articulating technical concepts to non-technical stakeholders and business goals to engineering teams.
- Education: Bachelor’s degree in business, Computer Science, or a related field.
Nice to Have
- Technical Proficiency: Practical experience or a strong understanding of Python, Java, Vue.js, or modern software development frameworks.
- Architectural Insight: Deeper familiarity with enterprise system architecture, API design, and cloud-based infrastructure components.
- Data Skills: Ability to write SQL queries and a deep understanding of data structures to perform independent analysis.
- AI Hands-on: Experience working with AI APIs (e.g., OpenAI, LangChain) or prompts engineering to achieve specific product outcomes.
- Domain Expertise: A professional background in Engineering or Quality Assurance (QA).
Perks & Benefits
- Grants for fitness and communication
- Healthy, free, provided snacks
