Product Lead – Fraud & Claims
IntraEdge · Hyderabad, Telangana, India
Apply & track with Apply EdgeJob Description – Product Lead – Fraud & Claims
The Product Lead will translate investigator expertise, operational procedures, industry knowledge, and business goals into scalable product experiences, intelligent workflows, and agentic solutions.The ideal candidate will work closely with Fraud & Claims Operations, Engineering, Data Science, Architecture, and Product teams to design, prototype, validate, and deliver solutions that improve investigator productivity, accelerate decision-making, reduce fraud losses, and enhance claims outcomes. The role requires a strong understanding of AI-driven decisioning, agentic workflows, human-in-the-loop models, explainability, governance, and regulatory requirements, particularly within financial services or other highly regulated environments.Key Responsibilities1. Product Vision & Solution DesignDefine and drive the product vision, strategy, workflows, and solution design for Fraud and Claims products.Start with business objectives, investigator expertise, operating procedures, and industry best practices to develop the initial product solution.Translate complex operational challenges into scalable product capabilities and user experiences.Develop proposed solutions before engaging business SMEs, using their feedback to validate, refine, and optimize the design.Identify opportunities to improve existing Fraud and Claims processes through automation, intelligent decisioning, and AI-enabled capabilities.Establish reusable product and design patterns that can be extended across multiple Fraud and Claims use cases.2. Lead Product & Architecture DesignDefine end-to-end solution designs covering:Product workflowsAgent behaviorsAI-driven decision strategiesDeterministic decisioningReasoning modelsOrchestrationInvestigator experiencesHuman-in-the-loop interactionsAI and human collaboration modelsDesign solutions that balance automation, accuracy, explainability, human oversight, security, and regulatory compliance.Determine when decisions should be driven by deterministic business rules versus AI/ML or agentic capabilities.Define appropriate human escalation and approval mechanisms for high-risk or complex scenarios.Collaborate with architects and engineering teams to ensure designs are technically feasible, scalable, secure, and production-ready.3. Agentic AI & Intelligent Workflow DesignDesign and operationalize AI agents and agentic workflows for Fraud and Claims operations.Define agent responsibilities, behaviors, decision points, escalation paths, and interaction models.Translate investigator knowledge and business processes into structured agent behaviors.Design orchestration models that enable multiple AI capabilities, systems, and human investigators to work together effectively.Establish appropriate human oversight mechanisms for AI-generated recommendations and decisions.Ensure AI-driven workflows are explainable, auditable, and aligned with enterprise risk and compliance requirements.Continuously evaluate opportunities to enhance investigator productivity through AI-assisted decision support and automation.4. Fraud & Claims Product DevelopmentWork closely with Fraud and Claims operations teams to understand investigator workflows, operational challenges, and decision-making processes.Convert investigator expertise into scalable product capabilities and reusable decision patterns.Design workflows supporting activities such as:Fraud detection and investigationAlert triageCase prioritizationInvestigation supportClaims assessmentEvidence gatheringDecision recommendationsEscalationsCase resolutionIdentify process inefficiencies and design solutions to reduce manual effort and improve investigation turnaround time.Ensure the product experience supports investigators with the right information, recommendations, context, and actions at the right time.5. Product Execution & Delivery LeadershipLead a cross-functional product team throughout the complete product lifecycle.Drive product and design decisions from initial concept through implementation and production deployment.Partner with Engineering, Data Science, Architecture, UX, Fraud Operations, Claims Operations, and other stakeholders.Ensure implementation remains aligned with the intended product vision, agent behaviors, investigator experience, and business outcomes.Make timely product decisions and resolve design or implementation ambiguity.Prioritize capabilities based on business value, operational impact, technical feasibility, risk, and regulatory considerations.Track product delivery, dependencies, risks, and key outcomes.6. Hands-On Design Through ExecutionRemain actively involved throughout implementation rather than treating product design as a one-time conceptual exercise.Work directly with engineering and data science teams to prototype and validate proposed solutions.Conduct iterative design sessions with Fraud and Claims operations.Analyze implementation feedback and operational results to refine workflows and product capabilities.Validate that delivered functionality matches the intended investigator experience and business objectives.Use experimentation and feedback to continuously improve product outcomes.7. Product Documentation & Implementation-Ready ArtifactsCreate clear and actionable product and architecture artifacts that can be directly consumed by engineering and implementation teams.Develop:Product vision and solution designsEnd-to-end workflowsAgent workflowsAgent behavior definitionsOrchestration modelsInteraction designsDecision frameworksHuman-in-the-loop modelsProduct specificationsProcess flowsPrioritized implementation backlogsAcceptance criteriaEnsure documentation clearly communicates business objectives, expected behavior, dependencies, and measurable outcomes.Maintain product documentation throughout the implementation lifecycle.8. Stakeholder CollaborationAct as a key product partner to Fraud and Claims business leaders and operational teams.Collaborate with:Fraud OperationsClaims OperationsEngineeringData ScienceArchitectureUX/UIRisk & ComplianceSecurityProduct ManagementFacilitate discussions between technical and business stakeholders.Present product strategies, solution designs, prototypes, and recommendations to senior leadership.Clearly communicate trade-offs, risks, dependencies, and expected business outcomes.9. Governance, Risk & ComplianceEnsure Fraud and Claims solutions comply with applicable regulatory, risk, privacy, security, and governance requirements.Design AI-enabled products with appropriate explainability and human oversight.Ensure automated and AI-assisted decisions can be appropriately reviewed and audited.Consider model risk, data privacy, security, bias, explainability, and operational risk when designing AI-driven capabilities.Partner with Risk, Compliance, Legal, and Security teams where required.Ensure product decisions are aligned with enterprise standards and risk tolerance.10. Build Internal Product CapabilityCoach and mentor Citizens’ product teams in designing and delivering agentic operational products.Establish repeatable methodologies for AI-enabled product discovery, design, and execution.Develop reusable patterns and frameworks that enable product teams to independently design future Fraud and Claims solutions.Promote strong product design practices across the organization.Encourage teams to focus on measurable business outcomes rather than requirements documentation alone.Share knowledge and best practices related to AI, agentic workflows, product strategy, and operational automation.Required Qualifications7+ years of experience in product management, product leadership, solution design, business transformation, or a closely related technology role.Strong experience designing and delivering enterprise-scale products and complex business workflows.Proven experience working with cross-functional teams across product, engineering, data science, architecture, and business operations.Strong ability to independently develop product concepts and solution designs from business objectives.Experience translating complex business processes and subject-matter expertise into scalable digital products.Strong understanding of product lifecycle management from concept and design through implementation and production.Experience creating implementation-ready product specifications, workflows, backlogs, and solution designs.Strong analytical, problem-solving, and decision-making skills.Excellent communication and stakeholder management skills.Ability to communicate complex technical and AI concepts to both technical and non-technical audiences.AI / Technology SkillsStrong understanding of Generative AI, AI agents, Agentic AI, and intelligent workflow automation.Understanding of LLM-powered applications and AI-assisted decision-making.Experience designing agent workflows and orchestration models.Understanding of deterministic versus AI-driven decision strategies.Familiarity with human-in-the-loop and human-in-the-agentic-loop architectures.Understanding of AI governance, explainability, responsible AI, and model risk.Familiarity with data science and machine learning concepts.Ability to collaborate effectively with engineering and data science teams on AI/ML solutions.Experience with APIs, cloud platforms, microservices, and enterprise application architecture is preferred.Fraud & Claims Domain ExperienceExperience in Fraud, Claims, Financial Services, Banking, Insurance, Payments, Risk, or related domains is highly preferred.Strong understanding of fraud investigation and/or claims operations.Experience working with investigators, operations teams, case management processes, or decision-support systems is an advantage.Understanding of fraud detection, risk scoring, alert management, case investigation, and decisioning processes is preferred.Preferred QualificationsExperience delivering products within a banking or highly regulated enterprise environment.Experience with AI/ML products or GenAI-enabled enterprise solutions.Experience designing workflow automation and decision-support platforms.Experience with Agile/Scrum product development methodologies.Experience working with distributed/global engineering teams.Experience with cloud-native technologies and modern enterprise architecture.Familiarity with product analytics and outcome-based product measurement.