> Markdown version of [/jobs/ext/3394777-product-owner-with-gen-ai](https://www.wearedevelopers.com/jobs/ext/3394777-product-owner-with-gen-ai). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Product Owner with Gen AI - **Company:** Techridge, Inc. - **Location:** United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Computer Literacy, Data Visualization, Fraud Prevention and Detection, Python (Programming Language), Scrum Methodology, Tensorflow, SQL Databases, Unstructured Data, Chatbots, Large Language Models, Prompt Engineering, Software Security, Model Validation, Generative AI - **Published:** September 2, 2026 - **Apply:** https://www.dice.com/job-detail/901171eb-3d72-4431-9104-82733a255b30 ## About the Role * Experience: 5+ years of experience as a product owner, preferably in financial services, banking, or credit cards. * AI/GenAI Knowledge: In-depth understanding of LLMs, prompt engineering, Retrieval-Augmented Generation (RAG), and AI development workflows. * Domain Expertise: Knowledge of credit card systems, fraud detection mechanisms, or personalized customer marketing. * Technical Literacy: Familiarity with Python, SQL, and data visualization tools, along with an understanding of AI/ML frameworks (e.g., TensorFlow, LangChain). * Agile Proficiency: Strong experience in Scrum or SAFe frameworks. ## Description A Product Owner experienced in managing Generative AI projects in the Credit Card business leveraging Large Language Models (LLMs) and generative techniques to enhance customer experience, automate internal workflows, and optimize fraud detection. Equipped with financial technology, data science, and agile product management to deliver secure, ethical, and high-value AI solutions., * GenAI Product Strategy: Define the roadmap for adopting Generative AI within credit card domains such as customer support bots, personalized marketing content generation, credit risk assessment, and fraud detection. * Backlog Management: Translate business needs into actionable user stories and acceptance criteria for data scientists and engineers. * Model Performance & Governance: Own the end-to-end performance of AI models, ensuring accuracy, reliability, and safety (e.g., mitigating hallucinations in LLMs). * Ethical & Regulatory Compliance: Ensure all GenAI initiatives comply with financial regulations (e.g., GDPR, data privacy laws) and adhere to internal AI governance frameworks. * Cross-functional Collaboration: Work closely with legal, compliance, risk management, and IT teams to ensure secure deployment of AI solutions. * Value Optimization: Evaluate the business impact of AI initiatives, measuring KPIs such as reduced customer service costs, higher engagement rates, or lower fraud rates., * GenAI-Powered Support: Developing LLM-powered chatbots that provide instant, human-like assistance for balance inquiries, disputes, and rewards questions. * Fraud Detection & Investigation: Using AI to analyze unstructured data for real-time risk assessment and automated fraud investigation reporting. * Personalization: Generating personalized rewards offers or financial insights for cardholders.