Important information years of experience: 7 years in product management, technical program management, or ai/ml product delivery job mode: full-time work mode: remote job summary the product manager – ai-powered saas solutions will lead the delivery and integration of ai and automation capabilities across a 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. 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 and duties 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, balancing immediate priorities with 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. Qualifications and skills 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). Role-specific 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. Technologies ai/ml platforms (tensorflow, pytorch, azure ml, aws sagemaker, etc.) Agile tools (jira, confluence, aha!) Data infrastructure (sql, snowflake, databricks, or similar) cloud ecosystems (aws, azure, gcp) skillset competencies ai/ml product management agile execution and delivery stakeholder collaboration data-driven decision making backlog prioritization continuous improvement about encora encora is the preferred digital engineering and modernization partner of some of the world’s leading enterprises and digital native companies. With over 9,000 experts in 47 offices and innovation labs worldwide, encora’s technology practices include product engineering & development, cloud services, quality engineering, devsecops, data & analytics, digital experience, cybersecurity, and ai & llm engineering. At encora, we hire professionals based solely on their skills and qualifications, and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality. J-18808-ljbffr