Open to full-time roles — Starting Jan 2027

Building infrastructurethat scales

CS graduate student at Northeastern. Distributed systems, event-driven architecture and cloud infrastructure — full stack when it needs it, and lately with agents and LLM orchestration in the mix.

Previously: SWE Co-op at Morgan Stanley, and four years at Psiog, most recently as Senior Software Engineer leading a distributed computing platform.

40.7513°N · 73.9786°W, NEW YORK, NY

[01]About

I build the unglamorous systems that everything else quietly depends on.

Most of my work is cloud and backend infrastructure — data pipelines, message buses, storage layers, the platforms other teams build on top of. The parts where latency and correctness both matter, and being wrong is expensive.

I've spent years further up the stack too — shipping React and .NET applications end to end — which is mostly why I care how the two halves meet. What holds my interest is systems under pressure: staying deterministic under chaos, moving events through without losing or duplicating them, migrating a live workload without downtime.

Lately that curiosity points at agent systems. Orchestrating LLM calls turns out to be a distributed-systems problem wearing a new hat — retries, idempotency, partial failure, keeping state consistent when a step times out halfway through. Same problems, unfamiliar costume.

FocusDistributed systems · Event-driven · Cloud

BuildingFull stack · Agents & LLM orchestration

StackAWS · Kafka · Java · C# · React · Python

Looking forFull-time SWE roles, starting January 2027

The stack behind
the things I build

Java

JavaScript

Kotlin

Python

TypeScript

Apache Kafka

Apache Camel

HTML

CSS

Stripe

React.js

Spring Boot

Angular

Node.js

.NET

SonarQube

DynamoDB

MS SQL Server

Oracle

PostgreSQL

MongoDB

Redis

AWS

GCP

Docker

Terraform

Kubernetes

GitHub

GitHub Copilot

Claude

Postman

[02]Featured case study

A lookup that took a minute. Nothing in the metrics said why.

My co-op project at Morgan Stanley. Counterparty lookups were taking 40 to 60 seconds because five active accounts were monopolizing the DynamoDB partitions. Three changes to the live table dropped that to 130 milliseconds. The historical workload moved off Dynamo entirely.

MANIFEST

StackAWS DynamoDB · Lambda · EventBridge · S3 · Glue (PySpark ETL, Crawler, Catalog) · Athena · Apache Camel · Kafka · Parquet · FIX

My roleSole owner — partitioning redesign, normalization model, end-to-end analytics pipeline

Scale~365GB historical backfill · ~60K offers/day post-normalization

FIX engine feeding DynamoDB partitions, with the JPM partition running hot while the rest sit idle

01Problem

Counterparty lookups took a minute.

The table looked fine.

PMs waited 40 to 60 seconds per counterparty to pull tax-harvest swap candidates. Aggregate DynamoDB metrics

looked healthy, so nothing flagged the real cause. Counterparty was effectively the partition key,

and five active accounts saturated their partitions while the rest of the table sat idle.

01Problem

Counterparty lookups took a minute. The table looked fine.

PMs waited 40 to 60 seconds per counterparty to pull tax-harvest swap candidates. Aggregate DynamoDB metrics looked healthy, so nothing flagged the real cause. Counterparty was effectively the partition key, and five active accounts saturated their partitions while the rest of the table sat idle.

02Approach

Two storage tiers. Live and historical stopped fighting.

Kept DynamoDB for the live intraday path: resharded on a synthetic partition key, normalized to one record per CUSIP — 2M writes a day collapsed to 60K — and added targeted GSIs for the queries the layout missed. Moved historical analytics off Dynamo entirely: Parquet on S3, partitioned by date, cataloged in Glue, read by Athena.

03Hard parts

Nothing downstream could switch on the same day.

Other teams read this through an API and re-point on their own release schedules, so the cutover could not be a single switch. Both tables took writes for 30 days while reads moved consumer by consumer, and the old endpoint stayed up behind them the whole time.

04Hard parts

The market doesn't close for a schema change.

Running 365GB as a single job means any failure restarts from zero. Glue handled the transform, Lambda dispatched one date partition at a time, and a control table tracked each partition — pending, in flight, done. Deterministic keys made a re-run overwrite rather than duplicate, so a failed partition cost one partition.

05Result

× faster reads. × fewer writes. Throttling gone.

Counterparty fetch went from 40-60 seconds to 130 milliseconds — a 300× speedup. Daily write volume dropped from 2 million records to 60 thousand after normalization. Historical queries that used to take minutes now return in under 5 seconds cold, around 25 milliseconds hot, with zero load on the live trading path.

[03]Projects

Things I've built on my own, outside of work.

Algorithmic Trading Bot

Systematic trading · ETF rotation

2026

Trades a rules-based ETF rotation strategy on an Alpaca paper account every weekday from a scheduled GitHub Actions job. The backtester and the live trader call the same pure strategy function, fills land at the next day's open, and order IDs are deterministic so a retried run can't trade twice. The strategy did well on 2013–2022 but trailed SPY on the 2023-onward holdout, which I set aside before running any backtest.

tradingbot.srikanthsharma.me

The bot's console: paper account value, current mode, the latest run's steps, and the backtest since 2013

Python
FastAPI
React
GitHub Actions

Live demo GitHub

[04]Experience

A short trail. More signal in the work above than in titles, but here's the shape.

Sep 2026 — PresentBoston, MA

Graduate Teaching Assistant
Sep 2026 — Present
Teaching Assistant for CSYE 6225: Network Structures and Cloud Computing under Prof. Tejas Parikh. Supporting students through office hours, assignment evaluations, and CI/CD workflows as they build and deploy a production-style web application on AWS with Terraform, GitHub Actions, load balancing and auto-scaling, serverless, and cloud security.

Jul 2025 — Jan 2026New York, NY

Software Engineer Co-op
Jul 2025 — Jan 2026
Designed and maintained real-time market data service infrastructure, building FIX protocol ingestion and Kafka streaming pipelines into DynamoDB alongside AWS archival ETL workflows.

Nov 2020 — Jun 2024

Senior Software Engineer
Feb 2023 — Jun 2024
Led the engineering team for an enterprise-grade distributed computing platform, orchestrating heavy compute and AI/ML workloads across heterogeneous cloud environments. Architected and shipped a foundational Function-as-a-Service (FaaS) capability, allowing data scientists to instantly deploy Python functions as live, auto-scaling microservice APIs.
Software Engineer
May 2021 — Jan 2023
Led an on-premises engagement for a Houston, TX-based energy infrastructure solutions provider, driving efforts to scale and modernize their software platform. Built customizable, cross-platform, and responsive web applications optimized for mobile and desktop using ReactJS, Electron, NodeJS, and .NET Core, backed by SQL Server and SQLite databases.
Associate Software Engineer
Nov 2020 — Apr 2021
Built REST APIs using MVC architecture and SQL Server databases while developing foundational web development skills across HTML5, CSS3, JavaScript, C#, and the .NET Framework.

[05]Recommendations

In their words, from people who've worked alongside me.

Jonathan Wong

Senior Software Engineer
Morgan Stanley · New York, NY

Managed me directlyMay 2026

What stood out most were his development and system design skills.

I mentored Srikanth during his co-op on the Fixed Income team at Morgan Stanley Investment Management, where he worked on municipal bond pre-trade execution services. He quickly developed a strong understanding of both the business context and processes behind municipal bonds, including how financial brokers send offers and bids through our systems.

Srikanth contributed meaningful improvements to one of our internal systems through architecture changes using DynamoDB and AWS, and gained significant hands-on experience with Kafka, demonstrating the ability to work effectively across distributed systems with a solid grasp of both technical and business contexts.

What stood out most were his development and system design skills. He consistently delivered well-structured solutions, showed a strong command of architectural principles, and proactively sought feedback during technical discussions.

I’m confident Srikanth will be a strong addition to any engineering team, particularly in roles that require both technical depth and an understanding of financial systems.

View on LinkedIn

Parigandha Nirgudkar

Senior Software Engineer
Mears Group, Inc. · Houston, TX

ClientMar 2025

His ability to think through complex problems and deliver clean, maintainable code made a real impact on our projects.

Srikanth was an invaluable contributor to our work at Mears Group Inc., where he played a key role in developing SafetyLink and SafetyHub, two applications designed to enhance crew safety and job tracking.

SafetyLink: Srikanth built intuitive front-end screens, integrated APIs, and created reusable UI components tailored to our business needs. He also implemented a text autocorrect feature using Electron.js, significantly improving data accuracy and user experience.

SafetyHub: He worked on the UI/UX and front-end development, ensuring seamless real-time data sync, job approval notifications, and cross-functional integrations, making it easier for supervisors to manage crew records.

Beyond his technical skills, Srikanth is proactive, detail-oriented, and great at building scalable solutions. His ability to think through complex problems and deliver clean, maintainable code made a real impact on our projects. I highly recommend him for any role that values strong front-end expertise and problem-solving!

View on LinkedIn

[06]Education

The paper trail. Two degrees, one continent change, and a steady pull toward software.

Expected Dec 2026

Master of Science in Computer Software Engineering

Boston, MA

Graduate coursework across systems, data, AI, and the web — building the foundation under the work above.

Web Design
Database Management
Java — Object-Oriented Programming
Program Structures & Algorithms
Network Structures & Cloud Computing
Generative AI
Financial Systems Engineering

Sep 2016 — May 2020

Bachelor of Technology in Aerospace Engineering

Coimbatore, India

Where the pull toward aerodynamics and aviation started. Project work focused on optimizing F1 car's inverted front wing for turbulent wake flow and ground effect — tuning the geometry to generate downforce for increased traction.

[07]Contact

Let'stalk.

Looking for a full-time role starting January 2027. Open to chatting about distributed systems, event-driven architecture, agent orchestration, or anything that has to stay up under load.

srikanthln98@gmail.com

GitHub

github.com/Sri-Ln

linkedin.com/in/sri-ln

Resume

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