Responsibilities:

Product Strategy & Roadmap:

Define product vision, strategy, and goals for AI-powered solutions, ensuring alignment with the companys overall objectives.
Drive product road-mapping efforts by 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 operational 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 balance engineering feasibility with user insights.

Effort Estimation & Prioritization:

Apply strong technical acumen and familiarity with AI development cycles to accurately scope and estimate the 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 the 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 across 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 ongoing iteration and improvement.

Qualifications :

Educational Background

Bachelors or Masters 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 such as machine learning, deep learning, and large language models.
Experience working with workflow automation tools and frameworks.
Ability to collaborate effectively with engineering teams and communicate technical concepts to both technical and non-technical stakeholders.

Product Management Experience:

3+ years of product management experience, preferably with AI-, ML-, or data-focused products.
Proven track record of delivering successful products in agile environments.
Strong ability to scope, estimate, and prioritize product features based on technical complexity and business impact.

Analytical & Communication Skills:

Excellent problem-solving skills with a strong, data-driven mindset.
Outstanding communication and presentation skills, with the ability to influence 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 such as AWS, Azure, or Google Cloud for AI/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.

Project Manager (AI Solutions)