Live opening · Posted 10 hours ago

Senior Manager — Industry Domain (Credit Decisioning)

Vymo · Mumbai, Maharashtra, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 10 hours ago
CompanyVymo
LocationMumbai, Maharashtra, India (On-site)
Work modeNo
SourceLinkedin
Listed10 hours ago

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About the role

Description supplied by the original job listing.

Vymo transforms how financial institutions manage their distribution networks and collections operations. Our AI-powered DMS and CMS platform serves 350,000+ users across 70+ global financial enterprises, enabling banks and insurers to optimize performance across their distribution channels, and empowering banks to drive operational excellence in collections.
Why Global Leaders Choose Vymo
Vymo partners with financial institutions through a comprehensive solution that combines deep domain expertise with cutting-edge technology. Our platform's human-centric design, coupled with enterprise-grade scalability and AI-powered intelligence, delivers measurable business outcomes while ensuring high user adoption and engagement.
Recognition & Trust
● Backed by $45M+ funding from Peak XV partners (formerly Sequoia), Emergence Capital, and Bertelsmann Investments.
● Trusted by leading global financial institutions including Berkshire Hathaway, AIA, AXA, SBI Life, HDFC Bank, Aditya Birla Capital, Tata AIA, ABSLI and many more!
● Recognized by Celent in their 2024 Distribution Management Solutions report, with an Advanced Functionality ranking.
● Featured in Gartner's Market Guide for Sales Engagement Applications and recognized as a
"Strong Performer" in Forrester's Sales Engagement Wave Report.
● Microsoft 'AI for All' award winner for innovation in artificial intelligence
The Role
Credit decisions at scale — whether a loan gets approved, at what rate, under what conditions — are governed by business rule engines and decision frameworks that have been refined over decades inside banks, NBFCs, and risk analytics firms. Vymo's agentic AI systems interact with, augment, and in some cases replace components of these decisioning frameworks.
Building the right system requires someone who understands how business rule engines actually work: how rules are authored, versioned, tested, and deployed; how credit policy translates into decision logic; where the standard engines fall short and where manual override is still the norm. That is this role.
You are the person who sits between a client's risk team and Vymo's product team — making sure that what is being built reflects how credit decisioning actually works in a regulated Indian financial institution, not how a software team imagines it works. You will carry domain knowledge from the BRE layer through to the underwriting policy and credit risk framework that sits above it.
The crux of this role: you know enough about credit decisioning and BRE architecture to know which questions, asked in which sequence, reveal how a client's decision engine actually works — and what Vymo needs to build to sit alongside it or replace it.
What You Will Do
1. Client Discovery — Decode the Decision Engine
Diagnose architectural realities and data flows by asking targeted questions that reveal system dependencies, latencies, and integration requirements.
Translate discovered logic gaps into actionable visual maps and precise engineering specifications for the product team.
2. Product Requirements — Translate Decisioning Logic Into What to Build
Translate credit decisioning and Business Rule Engine (BRE) logic into precise product specifications for Vymo's agentic layer, defining routing, rule execution, and human-in-the-loop interventions.
Validate technical assumptions against BFSI deployment cycles while mapping major BRE platforms (e.g., SAS, Experian, FICO) to ensure architectural accuracy.
3. GTM Support — Lend Credibility to the Technical Sales Conversation
Partner with sales teams in high-stakes sessions to provide deep architectural credibility and handle advanced technical inquiries regarding BRE and decisioning systems.
Act as a trusted advisor to client architects and risk heads, auditing technical proposals and developing GTM assets that address platform constraints and regulatory governance.
4. Industry Intelligence — Track How Decisioning Is Evolving
Track RBI regulatory changes—including the Model Risk Management Framework (MRMF) and AI explainability rules—alongside Indian BRE market trends to anticipate compliance demands.
Build a strong network of industry experts to validate core architecture choices and feed real-world market insights directly into the product roadmap.
What You will Bring
Experience & Fluency
Domain Background: Operational depth in credit decisioning across key sectors—whether coming from BRE vendors (SAS, FICO, Experian), bank/NBFC credit risk teams, underwriting operations, risk consulting, or credit bureaus.
BRE & Risk Architecture: Deep understanding of Business Rule Engine (BRE) architectures, rule authoring, champion-challenger frameworks, scorecard calibration, and baseline risk concepts ($PD/LGD/EAD$).
Origination & Integration Landscape: Practical knowledge of Loan Origination System (LOS) integration patterns, core platform configurations (e.g., PowerCurve, Blaze Advisor), and performance metrics like Straight Through Processing (STP) rates.
Regulatory & Compliance Context: Familiarity with RBI guidelines regarding algorithmic credit decisions, model risk management, explainability requirements, and cloud data localisation constraints.
Mindset & Core Traits
Architectural Inquiry: Driven by deep curiosity about how entire systems fit together, possessing the precise sequence of targeted questions that uncover how a client’s engine actually operates beneath the documentation.
Skeptical Practitioner: Operates with a healthy skepticism of stated architectures; validates system realities by analyzing deployment logs, rule histories, and exception reports rather than relying solely on official diagrams.
Policy-to-Logic Translation: Seamlessly bridges the gap between high-level credit policy language and structured, actionable rule engine engineering specifications.
Grounded Intellectual Humility: Explicitly understands the boundaries of personal technical knowledge, prioritizing accurate discovery and domain-expert networking over making unverified assumptions.

Work arrangement
No

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