New opportunity

Product Manager

myHQ · Bangalore, India

About this role

myHQ is seeking an AI-native Product Manager to join their product team and own key product areas end-to-end. The role involves driving the product roadmap from discovery and prioritization to shipping and measuring outcomes in a fast-paced, growth-stage environment. Responsibilities include writing detailed PRDs, creating functional prototypes, conducting user research, and leveraging AI tools to accelerate product workflows. You will collaborate cross-functionally with engineering, design, marketing, and operations to monitor product health and drive business impact. Requirements include 2-5 years of product management experience, an AI-native mindset with active use of LLMs and AI tools, strong analytical skills, and the ability to operate in ambiguity. Proficiency in SQL and product analytics tools like Mixpanel or Amplitude is required. Experience in SaaS, B2B, or marketplace products is considered a plus. The company culture emphasizes high ownership, a bias for action, and an AI-first approach to building products.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

Product ManagementPRD WritingAI ToolsLLMsPrototypingFigmaNo-code toolsSQLProduct AnalyticsMixpanelAmplitudeUser ResearchData AnalysisB2BB2C

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

End-to-End Product Ownership
The role requires taking full accountability for product areas from discovery through to shipping and outcome measurement. You must demonstrate a track record of managing the entire lifecycle rather than just executing tasks, specifically by aligning cross-functional teams on clear problem statements and business goals.
AI-Native Workflow Integration
You are expected to use LLMs and AI tools daily to accelerate discovery, PRD writing, prototyping, and competitive research. Preparation should focus on how you have practically integrated AI into your existing product management processes to increase speed and quality of output.
Data-Driven Decision Making
Proficiency in SQL and product analytics tools like Mixpanel or Amplitude is essential for monitoring product health. You must be prepared to discuss how you use behavioral data and funnels to validate product decisions and measure the impact of your features.

Likely challenges to think through

Operating in High-Ambiguity Environments
As a growth-stage company, you will face incomplete information and the need for rapid experimentation. The challenge is balancing the 'bias for action' with the need for rigorous, data-backed decisions. Prepare by reflecting on instances where you had to make high-stakes decisions with limited data.
Cross-Functional Alignment in a Fast-Paced Culture
You must collaborate with engineering, design, marketing, and operations while maintaining high ownership. The difficulty lies in communicating complex product intent clearly to diverse stakeholders. Prepare by practicing how you translate technical constraints into actionable PRDs and how you manage trade-offs when priorities conflict.

Practice your answers

Technical practice

Integrating AI into the Product Lifecycle

What to coverExplain how you would use LLMs or AI tools to accelerate specific stages of the product development lifecycle, such as PRD drafting, user research synthesis, or prototyping. Focus on how these tools improve speed and quality without sacrificing human oversight.

Data-Driven Prioritization in Marketplaces

What to coverDescribe your approach to prioritizing features for a marketplace product like myHQ, where you must balance the needs of both supply and demand. Discuss how you use product analytics tools like Mixpanel or Amplitude to validate your roadmap decisions.

SQL for Product Analytics

What to coverProvide an example of how you have used SQL to extract insights from raw data when standard dashboard tools were insufficient. Focus on how you translated these technical findings into actionable product improvements.

PRD Structure and Clarity

What to coverWhat are the essential components of a PRD that ensure engineering and design teams have enough context to execute effectively? Suggestion: Focus on clear problem statements, success metrics, and edge-case handling rather than just feature lists.

Prototyping for Rapid Experimentation

What to coverDiscuss your experience using no-code tools or Figma to create functional prototypes. Explain how you use these prototypes to test hypotheses with users before committing to full-scale engineering development.

Managing Product Health Metrics

What to coverHow do you define and monitor 'product health' for a service-based marketplace? Explain how you track funnels and KPIs to identify bottlenecks in the user journey and how you decide when to intervene.

Handling Ambiguity in Product Strategy

What to coverDescribe a time you had to make a significant product decision with incomplete information. Explain the framework you used to assess risk and how you communicated the trade-offs to stakeholders.

B2B vs B2C Product Nuances

What to coverGiven myHQ's focus on both enterprise leasing and individual day passes, how does your product management approach differ between B2B and B2C users? Address differences in sales cycles, user needs, and feedback loops.

Behavioural practice

Demonstrating High Ownership

What to coverDescribe a situation where you took end-to-end responsibility for a product outcome that went beyond your core tasks. Focus on the situation, the specific actions you took to ensure success, and the final business impact.

Bias for Action in Fast-Paced Environments

What to coverProvide an example of a time you had to move quickly to ship a feature or fix a problem. Explain how you balanced the need for speed with the necessity of maintaining product quality and user trust.

Navigating Cross-Functional Conflict

What to coverTell me about a time you had to align engineering, design, and operations on a contentious product decision. How did you use data or user research to build consensus and move the project forward?

Receiving and Implementing Feedback

What to coverThe company culture values open and direct communication. Describe a time you received critical feedback on a product decision and how you adjusted your strategy based on that input.

Sharpen your knowledge

Topics to prepare

AI-Native Product Development
The role requires integrating LLMs into the entire product lifecycle. Exercise: Document a recent product feature you managed and outline how you could have used AI tools to accelerate the discovery, PRD drafting, and competitive research phases. This is relevant because myHQ explicitly seeks an AI-first approach to building products.
Product Roadmap Prioritization in Ambiguity
The role involves owning a roadmap in a fast-paced environment. Exercise: Create a framework for prioritizing features when you have conflicting data and limited resources. Practice explaining your trade-offs clearly. This is relevant as the role requires operating in ambiguity and taking end-to-end ownership of outcomes.

Skills to revise

SQL and Product Analytics
Proficiency in SQL and tools like Mixpanel or Amplitude is required. Exercise: Write a SQL query to calculate the conversion rate of a user funnel and explain how you would use that data to identify a drop-off point in a marketplace product. This is essential for monitoring product health and driving business impact.
PRD Writing and Functional Prototyping
The role requires clear communication of product intent. Exercise: Draft a one-page PRD for a new feature (e.g., a meeting room booking flow) and create a low-fidelity prototype using a no-code tool or Figma. This is a core requirement for aligning engineering and design teams.

Your preparation checklist

Prepare an AI-Integrated Product Case Study
Select a past product feature you owned and document how you used LLMs or AI tools to accelerate your workflow. Prepare to explain how you used AI for user research, PRD drafting, or prototyping, and demonstrate the specific impact on speed or quality.
Demonstrate Analytical Proficiency with SQL and Metrics
Prepare a brief walkthrough of a time you used SQL or tools like Mixpanel/Amplitude to identify a product bottleneck. Be ready to explain the funnel analysis, the specific query or dashboard logic used, and the subsequent product decision you made based on that data.
Develop a Prototype for a Marketplace Feature
Create a functional prototype using Figma or a no-code tool for a hypothetical improvement to a marketplace product (e.g., a booking flow for meeting rooms). Focus on demonstrating your ability to translate a user problem into a tangible, testable solution.
Draft a Sample PRD for a Complex Problem
Prepare a concise, high-quality PRD that outlines a clear problem statement, user requirements, and success metrics. Ensure it highlights your ability to operate in ambiguity and communicate technical trade-offs to engineering and design teams.
Formulate Strategic Questions for the Interviewers
Prepare thoughtful questions regarding myHQ's current product roadmap, how they currently integrate AI into their internal product development lifecycle, and how they measure the success of their marketplace features in a growth-stage environment.

Availability last checked: 18 Oct 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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