Lead Product Manager

PayPal•Austin, TX

2d•$186,950 - $273,500•Hybrid

About The Position

PayPal, Inc. seeks Lead Product Manager in Austin, TX. This role involves leading the strategy, development, and go-to-market execution of innovative AI-powered products. The Lead Product Manager will define and execute the product vision and roadmap for enterprise generative AI solutions, identify market opportunities, and develop compelling business cases for new AI product initiatives. The role also includes conducting competitive analysis and market research, driving the adoption of AI tools within the PayPal ecosystem, and partnering with leadership to align product strategy with company objectives. Responsibilities include translating complex technical capabilities into clear product requirements and user stories, ensuring successful product development and delivery, defining success metrics and KPIs, and overseeing the development of product specifications, including data requirements and model performance criteria. The role also involves overseeing testing and validation of AI features, collaborating with customers to understand their needs and gather feedback, partnering with sales and marketing for go-to-market strategies, and working with legal and compliance teams to ensure responsible AI development practices. Building and maintaining relationships with key technology partners and vendors, guiding technical decisions around model selection, fine-tuning, and deployment, and overseeing the development of AI governance frameworks and monitoring systems are also key aspects of this position. Partial telecommuting is permitted from within a commutable distance.

Requirements

Master’s degree, or foreign equivalent, in Computer Science, Engineering, Data Science, Mathematics, Information Systems, Business Administration (with a technical concentration) or a related field plus three years of experience in the job offered or a related occupation.
Lead end-to-end product management for AI/ML or generative AI solutions in enterprise/SaaS environments. (3 years)
Build and deploy LLM-based features, including model selection, prompt/retrieval design, and scaling to production. (2 years)
Design and implement Retrieval-Augmented Generation (RAG) architectures with embeddings, vector databases, and guardrails. (2 years)
Execute model fine-tuning or parameter-efficient tuning (e.g., LoRA/PEFT) and optimize trade-offs in quality, latency, and cost. (2 years)
Conduct offline and online model evaluation using rubric-based assessments, human-in-the-loop reviews, and A/B testing. (2 years)
Define and track model performance metrics (quality, safety, latency, throughput, cost) and instrument telemetry monitoring. (3 years)
Identify and manage data requirements, including collection, labeling, PII handling, privacy-by-design, and data quality. (2 years)
Implement AI governance and risk management practices, including documentation, bias/fairness checks, drift monitoring, and incident response. (2 years)
Apply MLOps/LLMOps best practices and manage cloud ML infrastructure (AWS/GCP/Azure) for CI/CD, model lifecycle, and scalable inference. (2 years)
Ensure security, privacy, and compliance for AI features with GDPR/CCPA, data residency, DLP/redaction, and secure API productization. (2 years)

Responsibilities

Lead strategy, development, and go-to-market execution of innovative AI-powered products.
Define and execute the product vision and roadmap for enterprise generative AI solutions.
Identify market opportunities and develop compelling business cases for new AI product initiatives.
Lead competitive analysis and market research to inform product strategy.
Drive adoption of AI tools within PayPal ecosystem.
Partner with leadership to align product strategy with overall company objectives.
Translate complex technical capabilities into clear product requirements and user stories.
Ensure successful product development and delivery.
Define success metrics and KPis for AI product features.
Lead the development of product specifications, including data requirements and model performance criteria.
Oversee testing and validation of AI features, ensuring they meet quality and performance standards.
Collaborate with customers to understand their needs and gather feedback on AI solutions.
Partner with sales and marketing teams to develop go-to-market strategies.
Work with legal and compliance teams to ensure responsible AI development practices.
Build and maintain relationships with key technology partners and vendors.
Guide technical decisions around model selection, fine-tuning, and deployment.
Oversee the development of AI governance frameworks and monitoring systems.