Open to Global Remote · Mumbai, India

Jatin Khanda

Senior Product Manager in FinTech, Applied GenAI, and live service platforms. I build complex systems from scratch and ship them to scale. Currently at Morningstar, governing $250B AUM across 1.9M US retirement participants.

$250B AUM 1.9M Participants AWS Bedrock · Claude Opus Works IST & CST Daily 8+ Years PM

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About

I build platforms that govern real money and real scale.

I am a Senior Product Manager at Morningstar in Mumbai, where I own two roadmaps covering $250B in assets under management and 1.9M US retirement participants across Tier-1 clients including Empower and Capital Group.

I built Continuous Assurance from scratch — an internal audit platform that reruns the advice engine against original database parameters, flags equity allocation deltas above 5%, and saves millions annually in regulatory exposure. I did not inherit it. I conceived it, wrote the spec, and shipped it.

Before FinTech I scaled a consumer app to 1M concurrent users with zero downtime on launch day. Before that I built EMOTS, an AML transaction monitoring platform for real-time financial risk detection. That credential is what got me hired at Morningstar.

My AI design philosophy: functions own logic and calculations. AI owns the intelligence layer. I am deliberate about where models earn their place in a system, and I have shipped production pipelines on AWS Bedrock and Claude Opus that reflect this principle.

Algorithmic WealthTech AML / RegTech Applied GenAI Event-Driven Architecture Live Service Platforms Global Remote Mentor · AIC NMIMS Mumbai

Experience

What I have shipped

Three companies. Three domains. One pattern: I take complex systems from zero to live, measure the right things, and build for scale from day one.

Current

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Morningstar

Senior Product Manager

Nov 2024 – Present · Mumbai, India

95%+ reduction

in platform anomaly rate

Built Continuous Assurance from zero: reruns advice engine against original DB, flags deltas above 5%, saves millions annually
Lifted RM Optima adoption from 15% to 40% in 6 months across 1.9M accounts and $250B AUM
Shipped AWS Bedrock + Claude Opus pipeline: 8 modules, up to 16,000 transactions per client, auto-generating 30-second PDF summaries
Laterally promoted. Leads 8 to 10 engineers across Chicago and Mumbai

2023 – 2024

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Solytics Partners

Product Manager

Aug 2023 – Oct 2024 · Remote

3B rows

managed via no-code ETL pipeline

Led EMOTS modernisation from legacy monolith to real-time event-driven architecture for AML monitoring. This work led directly to the Morningstar hire
Engineered bi-directional FinCEN API integration for the US Corporate Transparency Act
Built no-code ETL pipeline on Kubernetes removing engineering dependency for data operations

2022 – 2023

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Es Magico Experiences

Product Manager · Mobile & B2C

Aug 2022 – Aug 2023 · Mumbai

$200K Day-1

1M concurrent users · zero downtime

Architected serverless AWS backend on independently scaling microservices. Zero downtime on a 1M-user launch. Parent company now valued at $350M
Led full Flutter-to-native iOS and Android migration for Keka HR across 7+ enterprise modules

AI & Platform Thinking

Functions own the logic. AI owns the intelligence layer.

I am deliberate about where AI earns its place in a system. Deterministic thresholds are explainable, auditable, and trustworthy. Models belong at the prediction and intelligence layer, not in the decisioning loop.

This philosophy has shaped every AI product I have shipped — from the AWS Bedrock pipeline at Morningstar generating 30-second PDF audit summaries, to the anomaly detection logic in Continuous Assurance that flags equity allocation deltas above 5%.

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AWS Bedrock · Claude Opus

Production GenAI pipeline with LLM guardrails, structured JSON output, and 30-second executive PDF summaries. Shipped at Morningstar across 8 audit modules.

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Event-Driven Architecture

Led full monolith-to-microservices modernisation at Solytics for real-time AML event processing. The same pattern applied to B2C at 1M concurrent users with independently scaling services.

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Spec Writing to Engineering

I write technical specifications that go directly to engineering teams. No middle-man translation. No scope ambiguity. From system architecture to rollout plan — all in one document.

Technical Specification

The kind of spec I write for engineering.

This document demonstrates how I think as a technical PM: starting with the real problem, translating it into a system architecture, and defining success metrics that actually matter. Grounded in firsthand domain experience and architectural patterns I have applied in production.

No invented formulas. No generic systems design. Just the logic — documented cleanly enough for an engineering team to build from.

Event-Driven Architecture Session State Engine AI at Prediction Layer Guardrail Metrics Staged Rollout

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Ranked Session Intelligence

Reducing Skill Disparity Drop-off in Competitive Matchmaking

Problem statement grounded in real player experience

Observable pre-churn session signals at match level

3-state engine with fully specified transition logic

5-step architecture: event bus through matchmaking layer

AI role defined at the predictive layer, not decisioning

Success metrics, guardrails, and staged rollout plan

Read the Spec →

Contact

Open to global remote opportunities.

Senior PM with a track record in FinTech, Applied GenAI, and live service platforms. Based in Mumbai. Works IST and CST daily. Available for interviews, calls, and trial projects.

Available now · IST & CST

✉️

Email jatin.khanda@gmail.com

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LinkedIn linkedin.com/in/jatinkhanda

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Phone · US +1 (605) 525-4615

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Phone · India +91 99999 37784