Job Description:

Job Title: Senior Product Manager Fraud (AI-First).

Company: SymphonyAI Financial Services.

Location: Bangalore, India (Hybrid).

Overview:

SymphonyAI Financial Services is seeking a Senior Product Manager (AI First) to define and build a market-leading fraud platform used by banks, insurers, payment providers, and gaming companies to detect, prevent, and manage fraud and financial crime at scale.

- This role is for a hands-on, deeply technical, domain-fluent product leader who understands that modern fraud is no longer a rules problem - it is a real-time decisioning, orchestration, and learning problem spanning detection, prevention, investigation, customer experience, and regulatory defensibility.

- You will own the end-to-end fraud product strategy, from real-time risk assessment and adaptive decisioning through investigation, recovery, and continuous learning.

- You will work at the intersection of AI, real-time systems, financial crime, and customer experience, and help define how fraud decisions are made across industries.

- This is not a maintenance role.

- This is a category-shaping role.

What You Will Own?

- You will be accountable for building a fraud product that:.

- Outperforms incumbents on accuracy, speed, and explainability.

- Scales across multiple verticals with different fraud economics.

- Balances loss prevention, customer friction, operational cost, and regulatory expectations.

- Evolves continuously as fraud tactics change.

Key Responsibilities:

Product Vision & Strategy (Category Leadership):

- Define and continuously refine the long-term product vision and multi-year roadmap for SymphonyAI's fraud platform.

- Articulate a clear AI-first and Agentic AI strategy for fraud, spanning:.

- Real-time scoring and decisioning.

- Adaptive controls and step-up actions.

- Alert generation, suppression, and prioritization.

- Automated and assisted investigations.

- Recovery, reimbursement, and learning loops.

- Position the fraud product as a platform, not a point solution - extensible across channels, geographies, and industries.

- Translate emerging fraud typologies, regulatory changes, and customer needs into differentiated product capabilities.

- Define how fraud integrates with the broader financial crime and risk ecosystem (AML, KYC/CDD, sanctions, investigations, customer risk, entity resolution).

Domain & Customer Leadership (Multi-Vertical Fraud Expertise):

- Act as a trusted domain expert for customers across:.

- Banking & Payments: cards, wires, ACH, RTP, instant payments, digital banking, account takeover, scams.

- Insurance: claims fraud, application fraud, policy abuse, first-party fraud.

- Gaming & Digital Platforms: bonus abuse, multi-accounting, collusion, bot-driven fraud, identity abuse.

- Deeply understand and shape fraud operating models, including:.

- Real-time vs post-event decisioning.

- Alert triage and prioritization.

- Analyst workflows and investigation quality.

- Customer communication and resolution.

- Chargebacks, claims, recovery, and reimbursement.

- QA, audit, governance, and regulatory oversight.

- Engage directly with fraud leaders, operations heads, risk executives, and product teams at Tier 1 and Tier 2 institutions to validate strategy and execution.

- Maintain strong awareness of global regulatory and network expectations (e.g., Reg E, PSD2/PSR, APP reimbursement regimes, card network rules, consumer protection and explainability requirements).

AI & Agentic AI Productization (Best-in-Class Execution):

- Partner with AI/ML and data science teams to deliver state-of-the-art fraud capabilities, including:.

- Real-time and near-real-time risk scoring.

- Behavioral, device, identity, and network-based detection.

- Alert clustering, suppression, and dynamic prioritization.

- Agent-driven evidence gathering across internal and external data sources.

- AI copilots for fraud analysts (recommended actions, summaries, decision rationales).

- Define and operationalize Agentic AI patterns for fraud, such as:.

- Autonomous resolution of low-risk events.

- Adaptive step-up authentication and control selection.

- Proactive scam detection and customer intervention.

- Continuous tuning driven by outcomes, feedback, and emerging threats.

- Own the balance between innovation, explainability, human oversight, and regulatory defensibility.

- Ensure all AI-driven decisions are transparent, auditable, and production-safe.

Platform, Architecture & Extensibility:

- Collaborate with UX, platform and engineering teams to ensure the fraud product is built on:.

- Real-time decision engines and streaming architectures.

- Configurable workflows and decision orchestration.

- Rich data models ontology and entity resolution.

- APIs and integration points for partners and customers.

- Enable customers to configure, extend, and evolve fraud strategies without vendor dependency.

- Support complex enterprise needs: high throughput, low latency, multi-tenant SaaS, data residency, permissions, and global deployments.

Product Execution & Delivery:

- Translate strategy into clear, prioritized roadmaps, epics, and user stories with measurable outcomes.

- Lead discovery, backlog refinement, sprint planning, and release execution with engineering, UX, and data science.

- Drive the full product lifecycle - from concept to scaled adoption.

- Partner with UX to deliver best-in-class analyst and operator experiences, including:

a. Real-time dashboards and queues:

b. Alert and case views.

c. Investigation timelines and evidence workspaces.

d. Decisioning, overrides, and controls.

e. Management reporting and governance tooling.

Go-To-Market & Commercial Impact?

- Partner with Sales, Marketing, and Customer Success on strategic deals, RFPs, workshops, and demos.

- Own product packaging, pricing input, ROI narratives, and competitive differentiation.

- Support Marketing with clear positioning and thought leadership on fraud, scams, and AI-driven prevention.

- Define and track success metrics, including:

a. Fraud loss reduction.

b. False positive and customer friction reduction.

c. Analyst productivity.

d. Recovery and reimbursement performance.

e. AI adoption and measurable impact.

Ideal Candidate Profile:

Experience:

- 7+ years of product management experience in fraud, risk, payments, fintech, regtech, or financial services.

- Deep hands-on experience with fraud detection, prevention, and investigation in at least one major vertical; exposure to multiple is a strong plus.

- Proven experience building AI-powered, real-time, enterprise-scale products.

- Track record of driving platform products, not just features, from concept to adoption.

- Experience working with large banks, insurers, gaming companies, or global platforms.

Skills & Competencies:

AI-First & Systems Thinking:

- Ability to reason from first principles about decisioning, orchestration, and learning systems.

- Comfort translating ML, LLMs, and decision engines into real-world product behavior.

Fraud & Risk Depth:

- Strong understanding of fraud economics, trade-offs, and customer impact.

- Fluency in explainability, governance, and operational controls.

Product Leadership:

- Proven ability to set direction, make hard trade-offs, and lead cross-functional teams.

- Data-driven, outcome-oriented decision maker.

User & Operator Empathy:

- Passion for building products that reduce friction while improving outcomes.

- Ability to simplify complex workflows without oversimplifying risk.

Communication & Influence:

- Clear, credible communicator with executives, customers, and technical teams.

- Comfortable representing the product externally with customers and partners.

Nice to Have:

- Experience with real-time decisioning, streaming systems, or payments infrastructure.

- Exposure to graph/network analytics, identity, device intelligence, or behavioral biometrics.

- Familiarity with Agentic AI frameworks or autonomous workflows.

- Background in data platforms or distributed systems.

What Success Looks Like (First 12-18 Months)?

- A clear, bold fraud product roadmap aligned with SymphonyAI's platform strategy.

- Delivery of step-change improvements in fraud accuracy, speed, and explainability.

- Strong adoption by flagship customers across multiple verticals.

- Demonstrated, quantified customer ROI and competitive wins.

- Recognition of SymphonyAI as a serious, modern fraud platform, not just a vendor.

Why SymphonyAI?

- Build the next generation of fraud and financial crime decisioning platforms.

- Work on mission-critical, real-time systems that directly impact customers and institutions.

- Shape a category alongside senior leaders in product, AI, and financial crime.