Product Lead – Fraud & Claims

IntraEdge; Hyderabad; Sur place; INR 3 500 000 - 5 500 000; Plein temps

Résumé du poste

IntraEdge in Hyderabad is seeking an experienced Product Lead - Fraud & Claims to steer the design and delivery of innovative solutions across Fraud and Claims operations. The role requires translating business objectives into scalable product experiences and intelligent workflows.

You will collaborate with Fraud & Claims Operations, Engineering, Data Science, Architecture, and Product teams to improve investigator productivity, speed decision-making, reduce losses, and enhance claims outcomes

Qualifications

• 7+ years in product management, product leadership, or related tech roles.
• Experience designing enterprise-scale products and complex workflows.
• Ability to translate business objectives into scalable product solutions.
• Strong understanding of AI-enabled product concepts and explainability.
• Familiarity with fraud, claims, risk, and regulatory considerations.

Responsabilités

• Define product vision and solution design for Fraud and Claims products.
• Lead a cross-functional product team through end-to-end delivery lifecycle.
• Collaborate with Fraud Ops, Claims Ops, Data Science, Architecture, and Security.
• Design agentic AI workflows with explainability and human oversight.

Connaissances

Product leadership

Stakeholder management

Cross-functional collaboration

AI concepts

Regulatory awareness

Outils

APIs

Cloud platforms

Microservices

Data workflows

Description du poste

Experience: 7+ Years

Employment Type: Full-Time

Role Overview

We are seeking an experienced Product Lead - Fraud & Claims to lead the design and delivery of innovative products and solutions across Fraud and Claims operations.

This role requires a strong product mindset with the ability to design products and solutions from business objectives rather than simply gathering requirements. 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 Responsibilities

1. Product Vision & Solution Design

• Define 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.
• Agent behaviors
• Deterministic decisioning
• Reasoning models
• Orchestration
• Human-in-the-loop interactions
• AI and human collaboration models
• Design 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 Design

• Design 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.
• Work 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 investigation
• Alert triage
• Claims assessment
• Evidence gathering
• Decision recommendations
• Escalations
• Identify 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 Leadership

• Lead 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 Execution

• Remain 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.
• Create clear and actionable product and architecture artifacts that can be directly consumed by engineering and implementation teams.
• Develop:
• Product vision and solution designs
• End-to-end workflows
• Decision frameworks
• Product specifications
• Process flows
• Prioritized implementation backlogs
• Acceptance criteria
• Ensure documentation clearly communicates business objectives, expected behavior, dependencies, and measurable outcomes.
• Maintain product documentation throughout the implementation lifecycle.

8. Stakeholder Collaboration

• Act as a key product partner to Fraud and Claims business leaders and operational teams.
• Collaborate with:
• Fraud Operations
• Claims Operations
• Data Science
• UX/UI
• Security
• Product Management
• Facilitate 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.
• Ensure 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 Capability

• Coach 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 Qualifications

• 7+ 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.
• Strong 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.
• Experience 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 Qualifications

• Experience 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.