AI Product Manager

Tiger Analytics Inc.

About The Position

Tiger Analytics is seeking an AI Product Manager to support large enterprise clients and lead the development of AI-powered products. The role defines product vision, strategy, and roadmaps aligned with business objectives and customer needs, identifying opportunities in Generative AI, LLMs, AI agents, machine learning, intelligent automation, and cloud-native platforms. The Product Manager leads products from ideation and requirements gathering through prototyping, development, testing, deployment, adoption, and continuous improvement, partnering with engineering, data science, design, business teams, and stakeholders. The role establishes product requirements, experiments, performance measures, and success metrics; manages AI-related risks; and communicates product strategy and business impact. The position offers work on strategic enterprise AI engagements, collaboration with global teams, continuous learning and AI upskilling, and career development in an entrepreneurial environment.

Requirements

At least 7 years of experience as an AI Product Manager, Product Manager, or in a related product leadership role, including delivery of AI-powered products to production.
Strong understanding of AI/ML concepts, Generative AI, LLMs, Retrieval-Augmented Generation (RAG), and AI agent architectures.
Experience defining AI product strategy, managing roadmaps, prioritizing features, and translating business needs into product requirements.
Demonstrated ability to lead AI initiatives from ideation and experimentation through deployment, adoption, and scaling.
Familiarity with LangChain, LangGraph, AWS Bedrock, OpenAI APIs, and cloud-based AI platforms.
Understanding of prompt engineering, model evaluation, experimentation methodologies, and AI performance optimization.
Experience working with engineering, data science, UX/UI, and business teams to deliver customer-centric AI solutions.
Strong analytical and problem-solving skills, including defining KPIs and evaluating product performance using data-driven insights.
Understanding of AI product challenges, including accuracy, hallucinations, scalability, latency, cost optimization, data privacy, and responsible AI practices.
Experience using AI-powered tools in product management workflows, including requirements gathering, research, prototyping, experimentation, and documentation.
Excellent stakeholder management, communication, presentation, and interpersonal skills, with the ability to influence cross-functional teams.
Ability to explain complex AI concepts as clear business value propositions and communicate solution approaches to technical and non-technical stakeholders.

Nice To Haves

Experience working in product-based organizations, technology consulting, or enterprise AI transformation initiatives.
Prior experience with cloud platforms, enterprise AI products, or applied AI research.

Responsibilities

Define and drive product vision, strategy, and roadmaps for AI-powered products aligned with business objectives and customer needs.
Identify and evaluate AI use cases involving Generative AI, LLMs, AI agents, and machine learning.
Collaborate with engineering, data science, design, and business teams to translate business requirements into product features and technical specifications.
Lead the end-to-end AI product lifecycle, from ideation and requirements gathering through prototyping, development, testing, deployment, and continuous improvement.
Define product requirements, user stories, acceptance criteria, and success metrics for AI-driven solutions.
Work with engineering teams to design and deliver AI-powered applications, agentic workflows, and intelligent automation solutions.
Design and drive experimentation strategies, including proofs of concept, prototypes, A/B testing, and iterative product enhancements.
Establish metrics for AI product performance, user adoption, customer experience, and return on investment.
Work with stakeholders to identify risks involving AI accuracy, hallucinations, data privacy, security, responsible AI, and regulatory compliance.
Monitor emerging AI technologies, industry trends, and best practices to identify product innovation opportunities.
Communicate product strategy, roadmaps, progress, and business impact to leadership and cross-functional stakeholders.
Foster innovation, experimentation, collaboration, and continuous learning across product and engineering teams.