Justdial - Product Manager - AutoSuggest (2-6 yrs)

Company Overview :

Justdial is Indias leading local search engine, providing comprehensive information across various categories to millions of users. Operating through its website, mobile apps, and telephone services, the platform bridges the gap between consumers and local businesses. With a massive database of listings and a deep-rooted presence in the Indian digital ecosystem, Justdial facilitates millions of transactions and inquiries daily, serving as a critical utility for both urban and semi-urban markets.

Role Overview :

As a Product Manager focusing on Search (AutoSuggest) and Vendor Onboarding, you will be responsible for enhancing the discovery experience for users while streamlining the digital entry point for service providers. You will work closely with engineering, data science, and operations teams to refine search algorithms and build intuitive onboarding workflows. Your efforts will directly impact the speed and accuracy of user queries and the efficiency of the vendor acquisition pipeline, ensuring a seamless marketplace experience at scale.

Key Responsibilities :

Search Autosuggest, Freetext, Voice & AI Enhancement :

- Own the full search product roadmap from core autosuggest and freetext relevance to voice query handling and AI-powered result enhancement.

- Drive the autosuggest experience: improve query completion quality, handle partial/misspelled inputs, and personalise suggestions based on user context and history.

- Own freetext search quality define ranking logic, reduce zero-result rates, handle long-tail queries, and improve precision and recall.

- Lead voice search product: define the end-to-end voice query flow, work with NLP teams on intent recognition, and ensure a seamless voice-to-results experience across platforms.

- Layer AI enhancements on top of core search including semantic search, embedding-based retrieval, query expansion, and LLM-assisted result re-ranking to improve suggestion quality and search relevance.

- Define and track the full suite of search quality metrics: query success rate, click-through rate, zero-result rate, autosuggest acceptance rate, voice recognition accuracy, and AI uplift metrics.

- Design and run A/B and multivariate experiments across all search modalities; synthesise results into clear roadmap decisions.

AI Chat Assistants & Chatbots :

- Own the product strategy and roadmap for AI-powered chat assistants and chatbot experiences across customer-facing surfaces.

- Define conversation design principles, user flows, and escalation paths balancing automation with seamless human handoff where needed.

- Work closely with LLM/NLP engineers to define prompt strategies, context management, tone and safety guardrails, and response quality benchmarks.

- Build and track chatbot performance metrics: containment rate, resolution rate, user satisfaction (CSAT), fallback rate, and session completion rate.

- Identify use cases where the chat assistant can intelligently connect to search, appointments, or vendor discovery creating a unified, conversational product experience.

- Run experiments to improve bot response quality, intent accuracy, and conversation completion and translate results into prompt, flow, or model improvements.

- Stay current on LLM product developments including tool-use, RAG-based chat, memory and context management, and agentic chat and apply relevant patterns to your roadmap.

Book Appointments & Vendor Onboarding :

- Has experience in end-to-end product strategy and execution for the book-an-appointment feature including discovery, scheduling flows, calendar syncing, confirmations, reminders, and cancellation/rescheduling handling.

- Lead the vendor onboarding module from sign-up and profile creation through service listing, availability setup, calendar syncing and go-live ensuring vendors can get started quickly and independently.

- Define and improve key funnel metrics: appointment conversion rate, vendor activation rate, time-to-first-booking, and drop-off points across both user and vendor journeys.

- Collaborate with sales, operations, vendor success, and support teams to surface friction points and translate them into product improvements.

- Explore opportunities to use the AI chat assistant to streamline appointment booking enabling users to book via conversation rather than only through traditional UI flows.

Required :

- 4 to 6 years of product management experience, with hands-on ownership of search products (autosuggest, freetext, or discovery) and/or AI-powered chat or chatbot products.

- Proven experience shipping and improving conversational AI products chat assistants, LLM-powered bots, or rule-based chatbot flows with measurable impact on resolution or engagement metrics.

- Solid understanding of how AI/ML powers search and chat including semantic search, embeddings, NLP intent recognition, LLM prompt design, RAG, and conversation state management.

- Proven track record of shipping end-to-end features with measurable business impact, including well-designed A/B experiments.

- Strong analytical mindset comfortable with SQL, funnel analysis, and product analytics tools.

- Ability to write clear, structured PRDs covering user flows, conversation flows, edge cases, and technical constraints.

- Experience with voice search or voice-based interfaces is a strong plus.

- Strong communication and stakeholder management skills across technical and non-technical audiences.

Nice to Have:

- Experience with agentic AI or tool-use patterns where the chatbot takes actions (e.g., booking an appointment, searching for vendors) on behalf of the user.

- Familiarity with conversation design best practices, including intent mapping, entity extraction, slot-filling, and fallback handling.

- Prior experience with appointment scheduling, booking platforms, or marketplace vendor onboarding.

- Exposure to responsible AI practices hallucination mitigation, bias detection, safety guardrails, and user trust in AI-generated responses.

- Experience evaluating or integrating third-party LLM APIs (e.g. OpenAI, Anthropic, Gemini) or chatbot platforms.

What You'll Bring :

- Deep curiosity about how people search and converse and a drive to make both experiences faster, smarter, and more effortless.

- The ability to think in systems: you see how search, chat, and transactional flows (appointments and onboarding) connect, and you design for the whole.

- Comfort bridging the gap between what AI can do and what users actually need you make AI invisible and outcomes obvious.

- Comfort with ambiguity, especially in probabilistic AI contexts where outputs vary and ground truth is hard to define.

- A collaborative spirit you treat ML engineers, data scientists, conversation designers, and ops partners as co-owners of outcomes.

- Rigor and speed in equal measure you move fast, instrument first, and celebrate learnings as much as wins.