Product Manager - Enterprise AI

As a Product Manager - Enterprise AI, you will play a crucial role in leading the transformation by defining and delivering AI tools that enhance voice intelligence, agent copilots, decision support systems, and risk engines. Your focus will be on supercharging our teams and establishing a new benchmark in fintech productivity. Your responsibilities will include defining the product vision and roadmap for our internal GenAI suite, which comprises voice copilots, risk intelligence agents, ops automation tools, regulatory AI assistants, and more. You will lead cross-functional teams to develop AI-powered workflows that reduce turnaround time, increase productivity, and enhance accuracy. Additionally, you will be responsible for making build vs. buy decisions utilizing vendors like OpenAI, Whisper, AssemblyAI, LangChain, among others. In this role, you will work hands-on with various AI technologies such as LLMs, embeddings, RAG pipelines, vector databases, and prompt tuning. It will be essential to design with explainability, fallback logic, and hallucination control as defaults. Monitoring success metrics like adoption rates, efficiency gains, and time saved will be crucial, and you will iterate quickly based on feedback to drive continuous improvement. Ensuring full alignment with regulatory bodies and internal compliance when deploying GenAI systems in critical workflows will be a key aspect of your role. You will also be responsible for maintaining cybersecurity standards as an integral part of product development, ensuring that products are built with security in mind from the outset. To be successful in this role, you should have at least 4+ years of product management experience, with at least 1 year in GenAI/ML/NLP-focused roles. A background in fintech, particularly in lending, collections, KYC, or regulatory operations, will be advantageous. A strong understanding of GenAI architecture, technical education background (in CS, Engineering, Data Science, or Applied Math), and experience working with data scientists, backend engineers, and legal/compliance teams are essential. An analytical mindset, the ability to define product KPIs, track outcomes, and excellent communication and stakeholder management skills are also crucial for excelling in this role.,