We are seeking a highly skilled Product Owner – AI-Powered Platform to lead the delivery and integration of AI capabilities across our suite of SaaS products. This role bridges product strategy with execution, translating business needs into technical requirements and ensuring that AI-driven features deliver measurable value.
About the Role:
As a Product Owner, you will drive the execution and delivery of AI-powered features, use cases, and platform capabilities across multiple SaaS products. You will translate business and product team requirements into actionable technical stories and sprint deliverables for data science and engineering teams.
Responsibilities:
* Drive the execution and delivery of AI-powered features, use cases, and platform capabilities across multiple SaaS products;
* Translate business and product team requirements into actionable technical stories and sprint deliverables for data science and engineering teams;
* Collaborate with cross-functional squads to embed AI and automation into existing product workflows;
* Define and manage the product backlog for AI feature delivery, striking a balance between immediate priorities and long-term platform scalability;
* Develop execution roadmaps, milestones, and release plans for model training, integration, and deployment across multiple product lines;
* Track key performance indicators (velocity, cycle time, release quality, adoption metrics) to ensure continuous improvement in delivery efficiency;
* Oversee post-deployment validation, ensuring model accuracy, reliability, and user experience alignment.
Requirements:
* Proven experience managing AI/ML-driven product initiatives within SaaS environments;
* Strong understanding of agile methodologies and end-to-end product lifecycle management;
* Exceptional communication skills with the ability to translate complex technical concepts into business terms;
* Data-driven mindset with the ability to define success metrics and measure adoption and performance;
* Experience coordinating multidisciplinary teams (engineering, data science, product, and UX).
Bonus Requirements:
* Experience with machine learning model lifecycle management—from concept to deployment;
* Familiarity with AI integration in enterprise SaaS systems, including automation, natural language processing (NLP), and predictive analytics;
* Understanding of MLOps, model monitoring, and continuous improvement practices;
* Ability to balance innovation with scalability and compliance requirements.
About Us:
We are a leading digital engineering and modernization partner of some of the world's leading enterprises and digital native companies. Our technology practices include Product Engineering & Development, Cloud Services, Quality Engineering, DevSecOps, Data & Analytics, Digital Experience, Cybersecurity, and AI & LLM Engineering.