Parul Bajpai Product Manager
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Hey, I'm Parul 👋

I'm a Product Manager at Adobe with 10+ years of experience building AI-powered products that operate at scale, think conversational platforms handling millions of interactions, GenAI integrations, and omnichannel experiences used by 130M+ customers weekly.

But here's what I've realized: most PM advice out there is either too theoretical or too startup-focused. I work in the trenches of enterprise AI product management every single day, and I bring that real, unfiltered experience into every session I run.
What I can help you with:
Whether you're breaking into product management, leveling up from APM to PM, or trying to navigate the fast-moving world of AI products, I've been there, and I can help you get there faster.

1. Crafting PRDs that engineering teams actually respect
2. Building roadmaps with clear prioritization frameworks
3. Understanding AI/ML concepts well enough to lead technical teams confidently
4. Preparing for PM interviews at top product companies
5. Transitioning into product from analyst, engineering, or consulting roles
6. Navigating stakeholder management and cross-functional influence

Why work with me:
I've mentored PMs across multiple squads at Adobe, spoken at the Product Leaders Day India Summit on building AI products, and taught product fundamentals to aspiring PMs through structured sessions. I don't give generic advice, I ask you the hard questions, challenge your thinking, and help you build the muscle to solve problems independently.

My sessions are direct, practical, and personalized. No fluff. No templates that don't apply to your situation. Just honest guidance based on what actually works.
A few things I've done that might be relevant to you:

1. Built and scaled LLM-powered platforms contributing to $16M ARR
2. Led AI roadmaps covering RAG, vector search, hallucination mitigation, and GenAI guardrails
3. Grown a product from 2% to 24% automation rate serving enterprise customers globally
4. Spoken publicly on AI product lessons at industry summits

If you're serious about growing as a product manager, especially in the AI space, let's talk. I'll meet you where you are and help you figure out the next right step.

Subjects

  • Product Management Beginner-Expert

Experience

  • Product Manager (Nov, 2019–Present) at Adobe Noida
    • Owned end-to-end product vision and roadmap for LLM-powered conversational platforms handling 3.7M+ interactions/quarter, driving 65% automation and $16M ARR
    • Collaborated with ML and Engineering on LLM integration, RAG architecture, vector search, grounding strategies, and hallucination mitigation, translating model performance signals into PRD updates and retraining triggers
    • Drove MCP and A2A orchestration with LangChain and AutoGen, making architecture-aware trade-offs across scale, performance, and extensibility for enterprise-grade reliability
    • Established AI evaluation and guardrail frameworks covering hallucination monitoring, content moderation, and model validation — improving CSAT by 18% and resolution rate by 8%
    • Implemented observability frameworks tracking 5+ quality metrics (hallucination rate, accuracy, p95 latency, cost per request), improving p95 latency by 30%; established SLA/SLO standards across 7 global language experiences
    • Benchmarked global GenAI platforms and LLM providers (OpenAI, Anthropic, Hugging Face) to identify innovation opportunities, informing 12-month roadmap prioritization
    • Integrated privacy and compliance safeguards across AI features — covering PII, GDPR/CCPA, and SOC-2 — partnering with Legal, Security, and Privacy teams for responsible AI governance
    • Defined PRDs, success metrics, and GTM strategy with Data Science, Engineering, Design, and Customer Success across geographies
    • Mentored 2-3 junior PMs on PRD writing, roadmap prioritization, and agile delivery across multiple product squads
    • Re-architected AI-driven personalized sales journeys across omnichannel touchpoints — routing, personalization, and channel expansion — generating $8M incremental ARR
    • Grew automation and deflection rate from 2% (2019) to 24% (2023), expanded to 80+ sub-intents across 9 languages serving Individual, Teams, and Enterprise segments — driving adoption to 130M customers weekly and $120M ARR influence
    • Pioneered roadmap for IVR phone bots and cross-surface conversational experiences, extending automation beyond web chat
    • Evolved platform APIs, tooling, and abstractions supporting AI-native development workflows and autonomous coding agent integrations
    • Partnered cross-functionally with Engineering, Data Science, and Customer Support to integrate GenAI and self-serve bot authoring, enabling scalable bot development
    • Championed integration of Adobe Answers and Agent Portal to enhance agent efficiency and user experience
    • Built high-velocity A/B testing pipeline across 5+ concurrent experiments, defining hypotheses, success metrics, and statistical significance thresholds to validate AI model changes pre-production
    • Leveraged SQL and Power BI to analyze user behavior funnels, identify drop-off patterns, and drive data-informed roadmap prioritization
    • Led cross-functional collaboration across 10+ teams including Engineering, Data Science, Design, Marketing, and Customer Success

    Skills: Product Lifecycle Management, Product Management, +14 skills

    Customer Experience Analyst

    Nov 2019 - Jan 2022 · 2 yrs 3 mos

    • Spearheaded end-to-end evolution of Adobe's Jarvis Bot — scaling from a single cancel-intent use case (2019) to a multi-lingual, GenAI-powered platform supporting 200+ products and 10+ customer types
    • Gathered requirements from ML engineers, data scientists, and AI application teams — translated complex technical needs into PRDs, success metrics, and prioritization frameworks
    • Partnered with 15+ engineers and data scientists to manage the full AI model lifecycle from experimentation to production; drove adoption through documentation, training, and internal evangelism
    • Defined product success metrics including automation rate, CSAT, ARR contribution, resolution rate, latency, and hallucination rate — enabling continuous platform optimization
    • Scaled AI customer engagement across 7 global languages and multiple product surfaces, enabling consistent automation worldwide
    • Partnered with enterprise and B2B stakeholders to translate operational workflows into scalable AI platform requirements, ensuring security and compliance

Education

  • MBA (Apr, 2024–Feb, 2026) from Indian Institute of Management, Lucknow - Noida campus
  • B.Tech (Aug, 2011–May, 2015) from GLA University, Mathura

Fee details

    ₹2,000–10,000/hour (US$21.05–105.25/hour)

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