Job Title: AI Solution Delivery Lead
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.
About the Job
Job Summary: We are seeking a seasoned Product Owner who can lead the delivery and integration of AI and automation 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.
Key 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.