Product Growth Manager | PGM - 1/ PGM - 2

Fynd is a frontier technology company. We started at the intersection of technology and retail because that is where technology was the least available. Over the years, we became one of India’s largest retail technology platforms. But retail was the entry point, not the boundary. Today, Fynd builds intelligent software that runs business operations. Not tools that help people work faster, but systems that absorb entire functions: manufacturing, marketing, logistics, commerce, quality control. We sit inside our customers’ businesses, harvest deep domain context, and build AI systems that operate autonomously. We are expanding from retail into manufacturing, generative media, physical AI, and healthcare. About the Role We are hiring a Product Growth Manager to lead initiatives at the intersection of retail, AI, and product execution. This role requires someone who can conceptualize and build AI-native features, scale them effectively, and drive adoption through experimentation, data insights, and structured execution. You will work closely with engineering, machine learning, product, and business teams to deliver AI-powered capabilities that solve real-world retail challenges. The ideal candidate has strong technical foundations, sharp product instincts, and a proven ability to operate with speed and ownership in high-growth environments. What will you do at Fynd? Build and launch AI-native product features in collaboration with ML and engineering teams. Drive product-led growth initiatives focused on activation, retention, and adoption. Translate AI/ML capabilities into scalable and intuitive product experiences. Work hands-on with model deployments, inference systems, and API integrations. Own end-to-end product execution—from problem discovery to roadmap delivery and post-launch iteration. Contribute to platform strategies that scale AI features from MVPs to production-grade adoption. Understand and influence product flows specific to retail, catalog systems, and commerce automation. Some Specific Requirements: AI and Technical Foundations Strong grasp of LLMs, embeddings, vector databases, RAG, and fine-tuning methods like LoRA and QLoRA. Hands-on experience with OpenAI, Hugging Face, LangChain, LlamaIndex, and production-grade AI tooling. Familiar with AI workflows using FastAPI, Docker, MLflow, and model serving via Ray or TorchServe. Comfortable working with GitHub, Git, and tools for managing models, code, and experiments. Good understanding of microservices, API design (REST/GraphQL), and scalable backend systems. Experienced in CI/CD setup for training and deploying ML models to production. Data and Analytics Proficient in SQL, BigQuery, and Looker Studio for data exploration and dashboards. Able to design KPIs, success metrics, and user journey insights for product analytics. Knowledge of tools like dbt, Airflow, and event-based platforms like PostHog or Mixpanel. Experience…