JTNC GROUP — Backend trading infrastructure for managing algorithmic trading signals and broker order routing.

Duration

Feb 2019 — Mar 2022

Type

Algorithmic Trading

Company

JTNC GROUP

Role

Backend Engineer

Location

U.S.A (Remote)

Rebuilt and maintained core trading infrastructure in Python, migrating from a monolithic architecture to a scalable microservice-based system deployed on Oracle Cloud, supporting platform operations across $1B+ AUM; engineered and maintained the QuantumFlow algorithmic trading engine optimising low-latency order routing, signal processing, and real-time broker integration across multiple asset classes.

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Project Context

Democratizing Institutional Tools for Retail

JTNC Group's mission is to bridge the gap between retail trading and institutional hedge-fund capabilities by providing proprietary predictive analytics and advanced market structure tools. The product relies on processing massive streams of real-time financial data to automate complex execution logic on behalf of individual investors.

During my tenure as a Backend Engineer, my core responsibility was architecting and rebuilding the trading infrastructure required to support this vision. This involved migrating legacy monolithic applications into a highly available microservices ecosystem capable of processing algorithmic signals at scale with minimal latency, supporting over $1B+ in AUM.

Architecting for Scale

Engineered for diverse accounts and robust growth

Engineered routing pipelines that adapted execution models based on the client's capital. For accounts under $25K, the system automatically routed single-leg options to comply with Pattern Day Trading (PDT) rules, while seamlessly transitioning to spread-based volatility strategies for larger portfolios.

Algorithmic Engine

Translating trading theory into reliable Python execution

A major technical challenge was translating JTNC's battle-tested trading models into a fully automated execution framework capable of analyzing market conditions and reacting with machine-speed precision.

Developed the backend services that aggregated market data to calculate daily probable price ranges with 70%+ confidence intervals, generating trading 'bands' to constrain the algorithm's operational window.

Engineering Contributions

Scalable Microservices Migration

Designed and executed the transition from a monolithic architecture to a highly scalable, microservice-based system deployed on Oracle Cloud, ensuring high availability and robust performance across $1B+ AUM.

Algorithmic Engine & Portal

Designed a client-facing portal and control center for managing algorithmic trading signals, investor accounts, and broker order routing — supporting multi-client portfolio management at scale.

Security & Compliance Infrastructure

Implemented end-to-end security including AES encryption, TLS/SSL, JWT, and RBAC with KYC/AML checks. Built real-time trade monitoring dashboards, alerting pipelines, and immutable audit logging ensuring full regulatory traceability.

CI/CD & Zero-Downtime Deployments

Established a mirrored staging environment with CI/CD automation for zero-downtime deployments and comprehensive regression testing across all platform services.

Python

React

Oracle Cloud

PostgreSQL

CI/CD

GitHub