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.