Intelligence Products and Systems Manager

World Business Lenders, LLC

. Manage, coach, and develop two Team Leads and four Analysts .

Posted 10/7/2026full-timeRemote • Costa Rica, El Salvador, Brazil, Argentina, Guatemala, NicaraguaSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in managing product portfolios, leading cross-functional teams, and delivering AI-enabled products from discovery to production. Proficient in product strategy, user adoption, and ensuring measurable business outcomes through effective oversight and integration.

Highest-signal resume keywords

AI Product DevelopmentTeam LeadershipProduct Roadmap ManagementUser Adoption StrategiesPerformance Monitoring

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Applied AI/MLData ScienceTechnical Product DevelopmentDecision SystemsProduct Requirements WritingPrototype DevelopmentModel EvaluationNLPPredictive Machine LearningAPI-Based AI Services

Soft Skills

CoachingCommunicationCollaborationProblem-SolvingPerformance Management

Tools & Technologies

Data EngineeringSoftware EngineeringBusiness ApplicationsModel Selection ToolsMonitoring Tools

Industry Keywords

Financial ServicesBusiness-User SupportData ReconciliationHuman-in-the-Loop SystemsModel Risk Management

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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

Benefits

Comp & perks

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