Product Manager – AI / GenAI (SaaS)
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Key skills for this role
About the Role
**Key Responsibilities** * Own the end\-to\-end product lifecycle for AI\-driven SaaS products and customer applications * Define and execute the product roadmap aligned with business and AI strategy * Translate customer and business needs into AI\-powered product features * Collaborate closely with engineering, architecture, and data science teams * Lead PRDs, user stories, wireframes, and acceptance criteria * Drive AI feature design, ensuring scalability, performance, an
Key Skills for This Role
Full Job Posting
Key Responsibilities
- Own the end-to-end product lifecycle for AI-driven SaaS products and customer applications
- Define and execute the product roadmap aligned with business and AI strategy
- Translate customer and business needs into AI-powered product features
- Collaborate closely with engineering, architecture, and data science teams
- Lead PRDs, user stories, wireframes, and acceptance criteria
- Drive AI feature design, ensuring scalability, performance, and usability
- Make trade-offs between model accuracy, latency, cost, and user experience
- Support architecture and design discussions for AI-enabled systems
- Ensure seamless integration of AI models into SaaS platforms and customer applications
- Monitor post-release performance, adoption, and AI model behavior
- Ensure compliance with data privacy, security, and ethical AI standards
Requirements
- 4–8 years of experience in Product Management or Technical Product roles
- Hands-on experience in software development, solution/system architecture, or product/UX design
- Proven experience working on SaaS products or customer-facing applications
- Strong understanding of scalable SaaS architecture, APIs, microservices, and cloud-based systems
- Good understanding of AI / ML concepts, GenAI fundamentals, LLMs, and AI APIs
- Experience with Agile / Scrum methodologies and writing detailed PRDs
- Ability to work closely with engineering teams and challenge technical decisions constructively
- Familiarity with AWS, Azure, or GCP environments
- Exposure to RAG pipelines, vector databases, and LLM orchestration is an advantage
- Strong problem-solving mindset with customer-centric thinking
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