Job Description
This role is a bridge between product strategy and execution. As the Product Owner of an AI-Powered SaaS Solution, you will lead the delivery and integration of AI and automation capabilities across a suite of SaaS products.
The ideal candidate will coordinate closely with data science, engineering, and product teams to build scalable, high-impact AI solutions that enhance user experience and business performance.
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 (e.g., recruiting, onboarding, performance, learning, analytics, and public safety);
* 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).
Preferred Qualifications
* 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 global digital engineering and modernization partner with over 9,000 experts worldwide. Our technology practices include Product Engineering & Development, Cloud Services, Quality Engineering, DevSecOps, Data & Analytics, Digital Experience, Cybersecurity, and AI & LLM Engineering.
At our company, we value diversity, equity, and inclusion, and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.