# Salman Syed Hussain

> Software Engineer | Fintech & Compliance | Backend Services, Real-Time Data, Cloud & DevOps (AWS, Kafka, Kubernetes)

Location: San Jose, California, United States
Profile: https://flows.cv/salmansyedhussain

Software Engineer specializing in fintech and compliance systems, with expertise in building scalable backend services, event-driven architectures, and real-time data pipelines. Experience spans projects in treasury management and embedded banking platforms at Stripe, as well as AML monitoring and regulatory compliance systems at J.P. Morgan.

Core strengths include:

Backend Development: Python (FastAPI, Django, Flask, SQLAlchemy, asyncio), Node.js

Frontend: React.js, TypeScript, Redux, Chart.js, Material UI

Data & Streaming: Apache Kafka, Spark, PySpark, Redis, Celery, RabbitMQ

Databases: PostgreSQL, MySQL, MongoDB

Cloud & DevOps: AWS (Lambda, EKS, S3, RDS, EC2, SQS), Docker, Kubernetes, Terraform, GitLab/GitHub Actions, Helm

Testing & Quality: Pytest, Selenium, Jest, Testcontainers, Postman, TDD

Focused on delivering secure, compliant, and highly available financial systems—covering areas such as ACH transfers, fraud detection, interest accruals, AML/KYC enforcement, and liquidity monitoring. Known for driving automation, clean architecture, and cross-functional collaboration to solve complex problems in real-time financial platforms.

## Work Experience
### Software Engineer @ Stripe
Jan 2024 – Present | United States
•	Developed backend services using Python (FastAPI, Django REST Framework) to manage embedded financial accounts, ACH transfers, interest accruals, and balance management via Stripe Treasury & Issuing APIs for U.S.-based fintech and SaaS platforms.
•	Designed RESTful and GraphQL APIs with FastAPI and Ariadne, enabling internal dashboards and customer portals to access real-time balances, transfer statuses, and transaction histories.
•	Integrated Stripe Webhooks with Kafka to process high-volume events including balance updates, ACH settlements, interest postings, and compliance alerts, ensuring low-latency and reliable event handling.
•	Built near real-time analytics pipelines using Apache Spark, PySpark, Kafka Streams, and Redis to monitor fund flows, average balances, interest accruals, and user-level transaction metrics, improving operational visibility.
•	Managed transactional data in PostgreSQL and stored flexible treasury metadata in MongoDB, supporting audit logs, compliance reporting, and webhook event tracking.
•	Developed interactive dashboards using React.js, TypeScript, Chart.js, and Material UI, empowering finance and compliance teams to track pending transfers, interest earned, ACH failures, and liquidity metrics.
•	Created microservices in Python and Node.js for fund reconciliation, fraud monitoring, and automated transfer scheduling, reducing manual intervention by 40%.
•	Deployed services with Docker on AWS EKS, using Lambda for lightweight treasury logic and SQS for reliable retry handling; implemented blue-green deployments for zero-downtime rollouts.
•	Handled background jobs like daily interest calculations, batch ACH processing, and scheduled reconciliation using Celery and RabbitMQ, ensuring timely and accurate financial operations.
•	Implemented OAuth2 and JWT authentication, maintaining role-based access control and compliance with PCI DSS, SOC 2, and GDPR standards.

### Software Engineer @ JPMorganChase
Jan 2020 – Jan 2023 | India
•	Designed and developed backend services using Python, Flask, and SQLAlchemy to power a high-volume compliance intelligence system that monitored trade and payment transactions in real time, ensuring adherence to AML and regulatory standards.
•	Built responsive, user-centric dashboards using React.js, TypeScript, Redux, and CSS3, enabling compliance teams to visualize flagged transactions, investigate alerts, trigger escalations, and track audit logs, improving operational transparency and reducing investigation time.
•	Developed modular microservices for AML rule enforcement, KYC verification, sanctions screening, and risk scoring, exposed via secure RESTful APIs to integrate seamlessly with both internal banking systems and external regulatory reporting platforms.
•	Implemented event-driven architecture with Apache Kafka to manage real-time workflows, including anomaly detection, transaction threshold breaches, and audit triggers, enabling faster response times to suspicious activity.
•	Designed a polyglot persistence model, leveraging MySQL for structured transactional data, MongoDB for semi-structured audit payloads, and Redis for low-latency rule/profile caching, which enhanced system throughput and reduced query response times by 40%.
•	Built a Node.js microservice to handle retry and replay logic for failed compliance events, ensuring data integrity, reliability, and reduced false negatives in monitoring pipelines.
•	Developed an asynchronous validation service using FastAPI and asyncio for parallel event replay and verification, which improved system resiliency and reduced downtime during peak transaction loads by 30%.
•	Collaborated with data science teams to integrate a machine learning model (scikit-learn, Pandas) for anomaly detection, reducing false positives by 25% and strengthening fraud detection accuracy.


## Education
### Master's degree in Computer Science
Campbellsville University


## Contact & Social
- LinkedIn: https://linkedin.com/in/salman35

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Source: https://flows.cv/salmansyedhussain
JSON Resume: https://flows.cv/salmansyedhussain/resume.json
Last updated: 2026-04-17