Aryann Dhir profile photo 1 on Tal

Aryann Dhir

Software Engineer @ Dutchess Management | Python, TypeScript, Java, Al Agents

Bengaluru

4+ years of work experience

Dutchess Management
Mar 20266 mosPresent

Remote

Interactive Brokers
Jul 20241 yr 8 mosFeb 2026

Mumbai, Maharashtra, India · Hybrid

1. Redis-Based Message Broker System • Built a priority queueing system using Redis as a message broker and a SpringBoot service that uses Lua scripting to interact with Redis and implement user-level exclusive message processing. • Leveraged Apache Camel to integrate multiple frameworks seamlessly, improving load balancing and overall system performance. • Impact: Increased computing throughput from 776 to 1905 rpm with 0 downtime, replacing a legacy Oracle table-based polling mechanism. • Technologies: Java, Redis, Lua, REST API, Oracle 2. Client Reporting Web Service • Replaced in-memory caching with a Redis-based cache to enable consistent data access across service instances. • Migrated from Oracle DB polling to an event-driven architecture using Amazon MSK, enabling real-time processing and reduced load on the database. • Redeveloped the reporting system to improve scalability and consistency for generating daily reports such as PortfolioAnalyst and Flex for 3.2M+ clients. • Impact: Enhanced scalability, reduced processing delays, and improved system resilience under high load. • Technologies: Java, Spring Boot, Redis, AWS MSK, Oracle SQL 3. AWR Report Analysis with LLM • Built an internal tool using Claude to extract actionable performance insights from AWR reports, enabling anomaly detection beyond standard tooling. • Impact: Accelerated issue identification and improved analysis efficiency; the tool was later adopted throughout the organisation. • Technologies: Claude, Prompt Engineering, Oracle AWR 4. Real-Time Elastic Monitoring • Real-time observability enabled by pushing the Kafka client and custom metrics into • Elastic Cloud using Micrometer and Elastic APM and visualising them via Kibana. • Impact: The visualisations helped in identifying system bottlenecks early and improved the speed of debugging critical issues. • Technologies: Java, Micrometer, Elastic Cloud, Kibana, Kafka
Interactive Brokers
Jun 20222 yrs 2 mosJul 2024

Mumbai, Maharashtra, India · Hybrid

- Introduced real-time application monitoring by pushing and indexing data in ElasticSearch. Collected Kafka client and custom metrics via MicroMeter and APM to enable faster data analysis and visualisation in Kibana, identifying bottlenecks in critical systems. - Deployed and integrated Redis as a message broker, utilising Lua scripting for enhanced message prioritisation and high processing throughput. - Implemented multiple APIs for data retrieval 6 hours prior to existing report for over 2 million clients - Encapsulated legacy applications to redesign the processing of over 20 million daily transactions and statement generation for all active clients.
GitHub
@aryanndhir

Aryann’s AI Stack

claude code
claude code
cursor
cursor
kimi
kimi
langchain
langchain
mcp
mcp
railway
railway

Education

SVKM's Narsee Monjee Institute of Management Studies (NMIMS)

Bachelor of Technology - BTech, Computer Science

SVKM's Narsee Monjee Institute of Management Studies (NMIMS)

20184 yrs2022

A Levels

Prabhavati Padamshi Soni International Junior College

20162 yrs2018

Join Aryann and 10k+ other professionals on

Tal Boss

Tal is the app where bosses meet engineers & builders directly, without middlemen

Download Tal Boss

Aryann Dhir on Tal

Headline

Software Engineer @ Dutchess Management | Python, TypeScript, Java, Al Agents

About

Aryann Dhir | https://aryanndhir.substack.com Feel free to email me at aryanndhir.work@gmail.com

Location

Bengaluru

AI stack

claude code

cursor

kimi

langchain

mcp

railway

Work experience

Software Engineer at Dutchess Management, Mar 2026 - Present · 6 mos, Remote

Software Engineer 2 at Interactive Brokers, Jul 2024 - Feb 2026 · 1 yr 8 mos, Mumbai, Maharashtra, India · Hybrid, 1. Redis-Based Message Broker System • Built a priority queueing system using Redis as a message broker and a SpringBoot service that uses Lua scripting to interact with Redis and implement user-level exclusive message processing. • Leveraged Apache Camel to integrate multiple frameworks seamlessly, improving load balancing and overall system performance. • Impact: Increased computing throughput from 776 to 1905 rpm with 0 downtime, replacing a legacy Oracle table-based polling mechanism. • Technologies: Java, Redis, Lua, REST API, Oracle 2. Client Reporting Web Service • Replaced in-memory caching with a Redis-based cache to enable consistent data access across service instances. • Migrated from Oracle DB polling to an event-driven architecture using Amazon MSK, enabling real-time processing and reduced load on the database. • Redeveloped the reporting system to improve scalability and consistency for generating daily reports such as PortfolioAnalyst and Flex for 3.2M+ clients. • Impact: Enhanced scalability, reduced processing delays, and improved system resilience under high load. • Technologies: Java, Spring Boot, Redis, AWS MSK, Oracle SQL 3. AWR Report Analysis with LLM • Built an internal tool using Claude to extract actionable performance insights from AWR reports, enabling anomaly detection beyond standard tooling. • Impact: Accelerated issue identification and improved analysis efficiency; the tool was later adopted throughout the organisation. • Technologies: Claude, Prompt Engineering, Oracle AWR 4. Real-Time Elastic Monitoring • Real-time observability enabled by pushing the Kafka client and custom metrics into • Elastic Cloud using Micrometer and Elastic APM and visualising them via Kibana. • Impact: The visualisations helped in identifying system bottlenecks early and improved the speed of debugging critical issues. • Technologies: Java, Micrometer, Elastic Cloud, Kibana, Kafka

Software Engineer 1 at Interactive Brokers, Jun 2022 - Jul 2024 · 2 yrs 2 mos, Mumbai, Maharashtra, India · Hybrid, - Introduced real-time application monitoring by pushing and indexing data in ElasticSearch. Collected Kafka client and custom metrics via MicroMeter and APM to enable faster data analysis and visualisation in Kibana, identifying bottlenecks in critical systems. - Deployed and integrated Redis as a message broker, utilising Lua scripting for enhanced message prioritisation and high processing throughput. - Implemented multiple APIs for data retrieval 6 hours prior to existing report for over 2 million clients - Encapsulated legacy applications to redesign the processing of over 20 million daily transactions and statement generation for all active clients.

Education

Bachelor of Technology - BTech, Computer Science, SVKM's Narsee Monjee Institute of Management Studies (NMIMS)

A Levels, Prabhavati Padamshi Soni International Junior College

Public links

github: https://github.com/aryanndhir