New opportunity

Principal Product Manager - Voice AI

HighLevel · India

About this role

The Principal Product Manager - Voice AI at HighLevel will lead product strategy and development for voice-based artificial intelligence solutions. This role is focused on driving the vision, roadmap, and execution of AI-powered voice features within the HighLevel platform. Responsibilities include defining product requirements, collaborating with engineering and design teams to deliver high-quality AI features, and ensuring the product meets the needs of users. The position is remote and based in India. Candidates must be authorized to work in India. The role requires strong product management expertise and a deep understanding of voice AI technologies to build impactful solutions that enhance the platform's capabilities.

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

Skills for this role

Product ManagementVoice AIStrategic PlanningProduct Strategy

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

Defining Voice AI Product Vision and Roadmap
As a Principal Product Manager, you are expected to set the strategic direction for voice-based AI features. You must demonstrate the ability to translate complex AI capabilities into a coherent product roadmap that aligns with HighLevel's platform goals and user needs.
Cross-Functional Execution and Collaboration
The role requires leading the end-to-end delivery of AI features by working closely with engineering and design teams. You must prioritize clear communication of product requirements to ensure technical feasibility and high-quality user experiences.

Likely challenges to think through

Balancing AI Innovation with Platform Stability
Integrating advanced voice AI into an existing platform often creates technical debt or performance trade-offs. Prepare to discuss how you manage the tension between deploying cutting-edge AI features and maintaining the reliability and performance of the core platform.
Translating Technical AI Complexity for Stakeholders
Voice AI involves significant technical nuance. A major challenge is effectively communicating the value and limitations of these technologies to non-technical stakeholders while ensuring engineering teams remain focused on high-impact, user-centric outcomes.

Practice your answers

Technical practice

Voice AI Product Strategy

What to coverExplain your framework for defining a product vision for voice-based AI. Focus on how you identify market needs, prioritize features based on user impact, and align the roadmap with broader platform objectives.

Voice AI Technology Stack

What to coverDiscuss your understanding of the core components of voice AI, such as ASR (Automatic Speech Recognition), TTS (Text-to-Speech), and NLU (Natural Language Understanding). Suggestion: Be prepared to discuss the trade-offs between latency, accuracy, and cost when selecting or building these components.

Measuring AI Feature Success

What to coverWhat key performance indicators (KPIs) would you use to measure the success of a new voice AI feature? Address both technical metrics like word error rate or latency and business metrics like user adoption or task completion rates.

Managing AI Development Lifecycle

What to coverDescribe your approach to collaborating with engineering and design teams during the development of AI features. Focus on how you manage the iterative nature of AI model training and testing while maintaining a predictable product roadmap.

User Experience in Voice Interfaces

What to coverHow do you design for the unique challenges of voice-first interactions, such as error handling, user feedback loops, and accessibility? Suggestion: Focus on how to maintain user trust and clarity when the AI fails to understand a command.

Data Privacy and Ethics in Voice AI

What to coverHow do you address data privacy and ethical considerations when building voice-based AI solutions? Discuss how you ensure compliance and build user trust regarding the collection and processing of voice data.

Scaling AI Solutions

What to coverWhat are the primary challenges in scaling voice AI features to a large user base? Address infrastructure considerations, model performance at scale, and the importance of continuous improvement through data feedback loops.

Behavioural practice

Navigating Cross-Functional Conflict

What to coverDescribe a situation where you had to align engineering, design, and business stakeholders on a complex AI product decision. Focus on how you communicated the trade-offs and reached a consensus.

Handling Product Ambiguity

What to coverProvide an example of a time you had to define a product strategy in an ambiguous or rapidly evolving technical space. Explain how you gathered information and made decisions to move the project forward.

Prioritization Under Pressure

What to coverTell me about a time you had to pivot your product roadmap due to technical limitations or changing market conditions. How did you manage stakeholder expectations and ensure the team remained focused on the most impactful work?

User-Centric Decision Making

What to coverDescribe a time you advocated for a user need that conflicted with technical or business constraints. How did you validate your position and what was the final outcome?

Sharpen your knowledge

Topics to prepare

Voice AI Product Strategy
Review the lifecycle of voice-based AI features, from speech-to-text accuracy to natural language understanding. Exercise: Draft a strategic roadmap for a hypothetical voice-AI feature that improves user engagement on a SaaS platform, focusing on how to measure success beyond simple latency metrics.
AI Product Lifecycle Management
Understand the unique challenges of managing AI products, including data privacy, model training, and iterative feedback loops. Exercise: Create a framework for gathering and prioritizing user feedback specifically for AI-generated voice outputs to ensure continuous quality improvement.

Skills to revise

Defining AI Product Requirements
Practice writing technical requirement documents (PRDs) that bridge the gap between user needs and engineering constraints for voice AI. Exercise: Write a PRD section detailing the functional requirements for a voice-activated task automation feature, including edge cases for ambient noise and accent variability.
Cross-functional AI Collaboration
Develop techniques for aligning engineering, design, and product teams on complex AI deliverables. Exercise: Simulate a sprint planning meeting where you must explain the trade-offs between model performance and development speed to non-technical stakeholders.

Your preparation checklist

Develop a Voice AI Product Strategy Framework
Prepare a presentation outlining how you would approach the product lifecycle for voice-based AI. Focus on identifying user pain points in existing voice platforms and how you would prioritize features to enhance the HighLevel ecosystem.
Prepare a Technical Case Study on Voice AI Implementation
Create a walkthrough of a previous project where you led the development of AI-powered features. Highlight your collaboration with engineering teams, the specific voice technologies utilized, and how you measured the success of the AI integration.
Analyze HighLevel Platform Capabilities
Research the current HighLevel platform to identify where voice AI could provide the most value. Prepare specific, informed questions regarding their current technical stack and the primary user segments they intend to target with new voice features.
Formulate a Roadmap for AI-Driven User Experience
Draft a hypothetical 6-month roadmap for a new voice AI feature. Include milestones for discovery, prototyping, cross-functional collaboration, and user feedback loops to demonstrate your ability to execute complex product visions.

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

KEEP EXPLORING

Similar AI jobs

Related skills and specializations in India. Matched to this role, not your profile.

Explore more jobs

Finding similar opportunities…