Senior Product Manager

Senior Product Manager About us Creative Information Technology Inc (CITI) is an esteemed IT enterprise renowned for its exceptional customer service and innovation.We serve both government and commercial sectors, offering a range of solutions such as Healthcare IT, Human Services, Identity Credentialing, Cloud Computing, and Big Data Analytics. With clients in the US and abroad, we hold key contract vehicles including GSA IT Schedule 70, NIH CIO-SP3, GSA Alliant, and DHS-Eagle II. Join us in driving growth and seizing new business opportunities. Role and Responsibilities The Senior Product Manager is responsible for leading the strategy, development, and delivery of AI-powered solutions in public sector platforms, with a focus on user value, policy alignment, and responsible innovation. This role acts as a strategic partner to cross-functional teams - data scientists, engineers, UX designers, and stakeholders - to build intelligent services that improve access, automation, and decision-making in systems like integrated eligibility (SNAP, TANF, Medicaid), child support, or case management. The ideal candidate brings deep experience in product lifecycle management, user-centered design, and a strong understanding of AI/ML technologies, including their risks and opportunities in regulated environments. Lead the product vision and roadmap for AI features aligned with agency goals, ethical standards, and technical feasibility. Identify opportunities to leverage AI (e.g., NLP, predictive models, classification, recommendations) to automate processes, enhance eligibility screenings, or assist workers and residents. Develop KPIs and success metrics for AI product components, balancing innovation with regulatory compliance and user trust. Translate AI opportunities into epics and user stories with well-defined acceptance criteria. Maintain and prioritize a backlog of AI/ML features, research spikes, experiments, and model integration tasks. Work closely with engineers and data scientists to define minimal viable models (MVMs), performance thresholds, and retraining strategies. Serve as the primary liaison between data science/AI engineering teams and policy or business stakeholders. Clearly communicate complex AI concepts (e.g., explainability, bias mitigation, model drift) in accessible terms. Facilitate feedback loops between user testing and model iteration. Collaborate with UX teams to ensure AI interactions (e.g., smart assistants, classifiers, chatbots) are intuitive and accessible. Conduct or commission user research to evaluate model output usability and relevance. Promote transparent, human-in-the-loop experiences where appropriate. Ensure AI solutions align with applicable data privacy laws (e.g., HIPAA, FERPA) and emerging AI governance standards. Partner with legal and policy teams to document risk assessments, explainability features, and audit trails. Contribute to guidelines for responsible AI use in public-facing products. Minimum Qualification This position requires a bachelor’s degree from an accredited college or university with a major in computer science, information systems, business, or other related scientific or technical discipline. Five (5) years of equivalent experience in a related field may be substituted for the bachelor’s degree. The proposed candidate must have at least five (5) years of experience working with statistical methods and quality standards. This individual must have a working QA/process knowledge and possess superior written and verbal communication skills. AI/ML testing or data science coursework/certification a plus. At least eight (8) years of software quality assurance experience, with increasing responsibility in testing enterprise systems. Minimum three (3) years working with or supporting projects involving AI/ML services or data science teams. Experience testing AI/ML model integration in enterprise applications (e.g., validation of model inferences, confidence scores, and response behaviors). Familiarity with ML model lifecycle, training/inference pipelines, and feedback loop workflows. Hands-on experience testing RESTful APIs, data APIs, or AWS-hosted AI services (e.g., SageMaker). Experience with automated test frameworks and performance testing tools (e.g., JMeter, PyTest, Selenium, Postman, Newman). Strong skills in writing and executing SQL for test data validation and pre/post inference checks. Experience with JSON-based payloads, OpenAPI/Swagger, and mock service tools. Ability to triage and analyze AI prediction issues related to data quality, model logic, or system design. Familiarity with ethical AI practices, including model bias testing, fairness, and transparency, is a plus. Excellent communication skills for bridging technical and non-technical stakeholders around complex AI test cases. Experience in Agile teams, working with tools like JIRA, Confluence, GitHub, TestRail, or similar. Preferred Qualifications The proposed candidate must have at least eight (8) years of information systems quality assurance experience.