▷ 15h Left Product Manager – Ai Solutions

Tipstat is at the forefront of technological innovation, building industry-leading solutions powered by artificial intelligence (AI) and workflow automation. We are seeking a dedicated and forward-thinking Product Manager with a strong computer science background and deep familiarity with AI (including large language models), workflow automation, and the end-to-end product life cycle. If you’re passionate about shaping the future of AI-driven products and have a talent for technical oversight and effort estimation, we want you on our team. RESPONSIBILITIES Product Strategy & Roadmap - Define product vision, strategy, and goals for AI-powered solutions, ensuring alignment with the company’s overall objectives. - Drive product roadmapping efforts, establishing clear timelines and priorities that account for evolving market needs and emerging AI technologies. AI & Automation Expertise - Leverage knowledge of AI, including large language models (LLMs), to ideate and evaluate product concepts. - Collaborate with AI scientists, engineers, and data scientists to design and implement state-of-the-art solutions (e.G., NLP, computer vision, recommendation engines). - Integrate workflow automation tools to enhance product functionality, streamline processes, and improve efficiency. Cross-Functional Collaboration - Work closely with engineering, design, and business stakeholders to translate requirements into detailed product specifications and user stories. - Foster a culture of collaboration and innovation, ensuring high-quality outputs that reflect engineering feasibility and user insights. Effort Estimation & Prioritization - Use strong technical acumen and familiarity with AI development cycles to accurately scope and estimate level of effort for product features. - Develop and maintain detailed project plans, anticipating risks and resource requirements early in the development process. User-Centric Development - Engage with customers and internal stakeholders to gather feedback on prototypes and existing solutions. - Continuously refine product requirements to meet user needs, enhance value delivery, and drive product adoption. Market & Competitive Analysis - Monitor competitive landscape, emerging AI trends, and new technologies to inform product decisions and maintain market leadership. - Identify new use cases and growth opportunities for AI-driven capabilities within various industries. Performance Measurement - Define and track key performance indicators (KPIs) to evaluate product success, including adoption rates, ROI, and customer satisfaction. - Develop data-driven recommendations and action plans for iteration and improvement. QUALIFICATIONS Educational Background - Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field. Equivalent practical experience will also be considered. Technical Experience - Demonstrated understanding of AI technologies (e.G., machine learning, deep learning, large language models). - Experience working with workflow automation tools and frameworks. - Ability to collaborate with engineering teams and effectively communicate technical concepts to both technical and non-technical stakeholders. Product Management Experience - 3+ years of product management experience, ideally with AI, ML, or data-focused products. - Track record of delivering successful products in agile environments. - Proven ability to scope, estimate, and prioritize product features based on technical complexity and business impact. Analytical & Communication Skills - Excellent problem-solving capabilities with a strong data-driven mindset. - Outstanding communication and presentation skills, capable of influencing cross-functional teams and senior leadership. Leadership & Stakeholder Management - Ability to manage multiple initiatives and stakeholders in a fast-paced environment. - Demonstrated initiative in driving projects forward proactively with minimal supervision. PREFERRED QUALIFICATIONS - Experience with cloud platforms (AWS, Azure, Google Cloud) for AI and ML model deployment. - Knowledge of MLOps best practices, including version control, CI/CD pipelines, and model monitoring. - Familiarity with data visualization tools and analytics platforms for product insights.