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.