
Product Manager – AI Solutions
4 weeks ago
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.
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