Intelligence Products and Systems Manager

• Manage, coach, and develop two Team Leads and four Analysts
• Own and prioritize product roadmaps based on user needs, business value, feasibility, data readiness, operational risk, and capacity
• Own the product portfolio and resource plan; hire, assess performance, develop Team Leads, and build succession coverage
• Maintain hands-on involvement in priority delivery
• Oversee product discovery, prototyping, acceptance, deployment into business use, monitoring, improvement, and retirement
• Ensure products integrate into business processes, support human oversight and user adoption, and deliver measurable outcomes
• Own product acceptance against agreed criteria and coordinate user enablement with Business Applications
• Develop product business cases and lead discovery through adoption
• Use evidence of value, feasibility, and risk to recommend which products to fund, scale, improve, or retire
• Establish controls for evaluation, documentation, explainability, privacy, security, change control, monitoring, and responsible use
• Coordinate required independent validation and business approval separately from development and product acceptance
• Own product performance monitoring, exception triage, escalation, and corrective-action follow-through
• Route model issues to Data Science, data issues to Data Engineering, and software defects to Software Engineering
• Coordinate user communication with Business Applications
• Review product outcomes with senior business leaders, challenge weak performance evidence, and adjust priorities and controls

• Relevant education or professional training in computer science, engineering, data science, mathematics, product management, or a related technical discipline is valued; a degree is not mandatory
• Twelve or more years of progressive experience across applied AI/ML, data science, software, analytics, decision systems, or technical product development
• At least five years of people leadership and meaningful experience leading Team Leads, managers, or senior technical/product staff
• Demonstrated delivery of AI-enabled or model-driven capabilities into real production use
• Demonstrated success building, scaling, or materially improving an applied intelligence, AI product, decision-product, or technical product capability
• Ability to coach Team Leads, develop technical/product talent, own and prioritize a portfolio, write clear product requirements and acceptance criteria, and deliver usable production products with cross-functional teams
• Experience making funding, sequencing, and trade-off decisions with senior business leaders
• Recent hands-on product and technical delivery; this is not a management-only role
• Experience taking AI-enabled or analytical products from ambiguous business problem through discovery, business case, prototype, requirements, acceptance criteria, production launch, user adoption, monitoring, and iterative improvement
• Experience with modern AI product development and evaluation, including model selection, API-based AI services, structured evaluation, retrieval/grounding, LLM workflow design, human-in-the-loop controls, and production observability
• Meaningful applied AI experience beyond generative AI
• Experience building decision-support or decisioning products combining data, calculations, rules, models, external data sources, and software
• Broad applied AI experience with predictive machine learning, rules and decision engines, optimization, document understanding/extraction, NLP, generative AI/LLMs, retrieval, agents or tool-using workflows, and hybrid human-in-the-loop systems
• Demonstrated production integration, monitoring, user adoption, and measurable business outcomes for AI-enabled or model-driven products
• Understanding of model and product risk, evaluation design, explainability, privacy, security, data quality, access controls, monitoring, drift or degradation, exception handling, human oversight, and responsible use
• Ability to communicate technical choices and risk clearly to senior business leaders and translate business requirements into precise direction for data science and engineering teams
• Ability to distinguish product ownership from data science and software engineering ownership
• Ability to lead product discovery, develop prototypes, evaluate applied AI approaches, define product behavior and acceptance criteria, challenge model evidence, and investigate performance issues
• Ability to build a durable organization through hiring, coaching, delegation, roadmap discipline, standards, performance management, and development of Team Leads
• Experience in lending or financial services, business-user support, and data reconciliation preferred

• Compensation in USD
• Paid time off (PTO)
• Fully remote work environment