Level: Product Manager 2
At IDfy, TrustStack isn't a back-end utility — it's the trust and data platform that sits underneath every IDfy product. It verifies people and businesses against authoritative sources, reads and checks documents, confirms that a face is real and belongs to the right person, and detects fraud and tampering. You'll spend real time with clients, lead Engineering, DevOps, and Data Science without formal authority, and build prototypes yourself when that's the fastest way to an answer. Fraud Intelligence — detecting fraud and tampering across documents, faces, and identities, and turning those signals into products clients rely on
Model Quality & Reliability — knowing how our models and data sources perform in production, and acting before a client feels a problem
Document Intelligence — helping clients and internal teams read, understand, and verify any document faster
Global Coverage — taking capabilities to new markets and cross-border use cases, and building geography-specific capabilities
Have a B.Tech from a Tier-1 engineering institute (IIT / NIT / BITS)
Have 4–5 years of experience, with hands-on product management on technical, integration-heavy, or data-centric B2B products — developer platforms, data infrastructure, ML-powered products, or B2B SaaS (product and consulting backgrounds both welcome)
Are strongly analytical — comfortable crunching data, working with SQL, logs, dashboards, and model evaluation metrics, and making a call from evidence
Have high agency and a bias for action — you'd rather ship a version on Friday and learn than debate it for a month, and you can show us examples




Speak Engineering, DevOps, and Data Science fluently — engineers trust your judgement on integrations, data pipelines, and trade-offs
Have led without authority — you've rallied engineers and data scientists who didn't report to you around a shared deadline and outcome
Bonus points if you've:
Worked on B2B integrations (at any point in your career — not necessarily in your current role)
Built or shipped work in identity verification, fraud, risk, or fintech for banks and NBFCs
Worked closely with ML teams on model evaluation, monitoring, or releases
Had a founding or early-stage startup stint, or worked as an engineer or data scientist before moving into product
Prototyping before you spec — using AI coding tools to build a working prototype, demo, or dashboard and putting it in front of a client or engineer before writing a long document
Going deep on model and product performance — instrumenting metrics, evaluating precision, recall, drift, and latency, and making data-driven trade-offs between accuracy, speed, and cost
Leading cross-functionally — aligning Engineering, Data Science/ML, DevOps, Sales, Legal, and InfoSec teams that don't report to you, without letting anyone become a bottleneck
Shipping and measuring — taking features from idea to production to adoption, and tracking whether what you shipped moved the goal
Because this is where trust is built with data. Problems that don't have answers yet — fraud intelligence and AI-native trust infrastructure for financial services, across India and Asia
A robust technical bench — dedicated Engineering and Data Science teams

📌 Product and Tech Manager (Mumbai)
🏢 IDfy
📍 Mumbai