Principal Product Manager

About MoEngage:

MoEngage is an insights-led customer engagement platform trusted by 1,350+ global consumer brands, including McAfee, Flipkart, Domino's, Nestle, Deutsche Telekom, and OYO. MoEngage combines data from multiple sources to help brands gain a 360-degree view of their customers.

MoEngage Analytics arms marketers and product owners with insights into customer behavior. Brands can leverage MoEngage Personalize to orchestrate journeys and build 1:1 conversations across the website, mobile, email, social, and messaging channels. MoEngage Inform, the transactional messaging infrastructure, helps unify promotional and transactional communication to a single platform for better insights and lower costs. MoEngage's AI Suite helps marketers develop winning copies and creatives, optimize campaigns and channels that boost engagement, and help with faster execution.

For over a decade, consumer brands in 60+ countries have been using MoEngage to power digital experiences for over a billion monthly customers. With offices in 15 countries, MoEngage is backed by Goldman Sachs Asset Management, B Capital, Steadview Capital, Multiples Private Equity, Eight Roads, F-Prime Capital, Matrix Partners, Ventureast, and Helion Ventures.

MoEngage was named a Contender in The Forrester Wave™: Real-Time Interaction Management, Q1 2024 report, and Strong Performer in The Forrester Wave™ 2023 report. MoEngage was also featured as a Leader in the IDC MarketScape: Worldwide Omni-Channel Marketing Platforms for B2C Enterprises 2023.

About the Role;

As a Senior/Principal Product Manager for Recommendations, Data Science, you will own the Intelligence layer of MoEngage. You will be responsible for building world-class recommendation engines that predict user behavior and leveraging Generative AI to bridge the gap between insight and action.

You will work at the conflux of Big Data and Artificial Intelligence, collaborating closely with Data Scientists and Engineers to build products that help marketers answer: What should I recommend to this user, and what is the best way to say it

Roles & Responsibilities

• Define Product Vision & Strategy: Own the end-to-end roadmap for the AI/ML pod, focusing on predictive recommendation systems, affinity modeling, and Generative AI applications.
• Lead the AI Revolution: Identify and implement ML and GenAI use cases that streamline the marketing workflow—from automated copy generation to AI-assisted journey building.
• Scale Recommendation Engines: Drive the strategy for our 1:1 personalization engine, ensuring it can handle trillions of data points to deliver real-time, relevant product and content recommendations.
• Collaborate with Data Science: Partner with the DS team to translate complex models (XGBoost, Reinforcement Learning, LLMs) into intuitive product features that non-technical marketers can use.
• Data-Driven Decision Making: Live and breathe metrics. Define and monitor KPIs for recommendation accuracy, conversion uplift, and AI-driven efficiency.
• Be the Customer's Voice: Conduct deep user research to understand the pain points of growth marketers and product owners, turning these insights into scalable AI solution.
• Cross-Functional Leadership: Work with GTM teams (Sales, CS, Marketing) to ensure product delivery, market adoption, and a clear competitive advantage in the MarTech space.

Requirements

• 5+ years for Senior Product Manager / 7+ years for Principal Product Manager in Product Management, specifically within B2B SaaS, MarTech, or Data/Analytics companies.
• AI/ML Domain Expertise: Proven track record of shipping ML-driven features. You should be comfortable discussing data models, APIs, and the nuances of LLMs with engineers.
• Analytical Mindset: Expert-level proficiency in SQL and data analysis. You don't just look at dashboards; you hunt for patterns in raw data.
• Customer-Centricity: A history of talking to customers and translating ambiguous problems into clear, concise product requirements and user stories.
• High Bias for Action: You thrive in a fast-paced environment, can prioritize ruthlessly, and take full ownership of your product area from ideation to GTM.
• Technical Education: Bachelor's degree in Computer Science, Engineering, or a related field (MBA/Master's is a plus).

Bonus Points:

• Direct experience building ML or Recommender Systems or Discovery engines.
• Familiarity with LangChain, LlamaIndex, or building Agentic workflows using LLMs.
• Previous experience in the Customer Data Platform (CDP) or Marketing Automation space.
• MBA or advanced technical degree.