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We are seeking an experienced AI Product Manager to join our fast-growing team. You will own the end-to-end lifecycle of AI-powered products, from ideation through launch and iteration. Your primary focus will be to drive the development, release, and continuous improvement of AI apps—such as ticket triage, ticket QA, sentiment analysis, and conversational BI—ensuring they deliver measurable value to our MSP clients.
Job Responsibility:
Product Ownership: Lead the strategy, roadmap, and execution for AI-powered apps, including ticket triage, ticket QA, and sentiment analysis, ensuring alignment with company goals and client needs
Cross-functional Collaboration: Work closely with engineering, data science, design, marketing, and sales to deliver high-quality products on schedule
Client-Centric Development: Engage with MSP clients and internal stakeholders to gather requirements, validate product value, and ensure exceptional user experience
Market Analysis: Monitor industry trends, competitor offerings, and customer feedback to inform product strategy and feature prioritization
Performance Tracking: Define and track key product metrics, using data-driven insights to guide product improvements and report on outcomes
Documentation & Training: Ensure clear product documentation and support materials are available for both internal teams and clients
Prototyping & Iteration: Lead rapid prototyping and MVP releases, especially for new AI-driven features and apps, leveraging client feedback for continuous improvement
Requirements:
3+ years of product management experience, preferably in SaaS, AI, or automation products
Demonstrated success managing GenAI/ML-powered/AI agents products from concept to launch
Strong technical acumen and experience working with data science and engineering teams
Excellent communication, collaboration, and client management skills
Analytical mindset with a passion for data-driven decision-making
Experience working in agile environments and managing multiple priorities
Nice to have:
Experience with cloud AI platforms (Azure OpenAI, AWS) and usage-based billing models is highly desirable