Ayush Saxena

Hi, I’m

Ayush Saxena

Lead Developer at PivotMoney

I build dependable backend systems, financial infrastructure and AI tooling.

Get in touch View resume

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Ayush Saxena

About me

I’m Ayush, a software engineer focused on backend systems, financial infrastructure, and AI tooling. I enjoy taking a product from an early idea through to software that people use and depend on.

Currently, I lead engineering at PivotMoney, building an investing platform for Indian and overseas investors. My work spans financial integrations, transaction workflows, reconciliation, and production infrastructure. Previously at Turing, I built APIs and evaluation tools for large language model workflows.

I work primarily with Python, Django, PostgreSQL, and React. I’m particularly interested in the details that make systems dependable: how data stays consistent, how failures are handled, and how a system can be understood when something goes wrong.

I graduated from IIT Kharagpur in 2024 with a dual B.Tech and M.Tech degree.

Experience

PivotMoney

Lead Developer

Mar 2026 – Present

I lead a team of more than ten engineers building a regulated investing platform for mutual funds, US stocks and wealth tracking, and own twelve core areas of the product from the backend to the React web app.

I integrated BSE StAR MF, India’s largest mutual-fund exchange, and brought payment confirmation down from 24 hours to under five minutes. I designed an append-only ledger with two-phase settlement that recovered more than 50,000 hidden transactions for over 10,000 users, and led the launches of US stock trading and open-banking wealth tracking. I also set up our production stack on Google Cloud, with CI/CD, 140+ kill switches and a test suite of more than 21,000 tests.

  • Python
  • Django
  • PostgreSQL
  • Celery
  • React
  • GCP
  • Gemini

Turing

Software Developer

Jun 2024 – Nov 2025

I built and tuned the Python and FastAPI services on Kubernetes that orchestrate distributed LLM training jobs, cutting API timeouts by half under heavy load. I also built a real-time React dashboard for validating model-generated code during training, and automated CI/CD for the ML infrastructure on AWS, removing about 70% of the manual work.

  • Python
  • FastAPI
  • Kubernetes
  • React
  • AWS

TransOrg Analytics

Software Developer Intern

Jun 2022 – Jul 2023

I built and maintained the Django services behind TransOrg Analytics and Pickl.AI for more than 10,000 users, and ran their AWS infrastructure at 99.9% uptime. I made deployments 40% faster, sped up API responses by 30%, and replaced a paid analytics service with an in-house one at 70% lower cost.

  • Django
  • DRF
  • AWS
  • PostgreSQL

Web Prism IT

Software Developer Intern

May 2021 – Jul 2021

My first internship. I connected React frontends to Django REST Framework backends for e-commerce clients, and wrote and documented the APIs between them.

  • React
  • Django REST Framework

Projects

SwissPlat

Founding engineer

A B2B marketplace that matches buyers with the right suppliers. I built supplier matching with retrieval-augmented generation on pgvector, and automated requests for quotation so buyers get standardized, AI-summarized quotes, cutting manual negotiation time by 40%. I also added per-customer data isolation and guardrails against prompt injection.

  • Django
  • pgvector
  • LangChain
  • OpenAI
  • Celery

Govvens

Ticketing platform

A ticketing platform for keeping stadium crowds safe. Fans verify their identity with eKYC and face recognition in under two seconds at the gate, get an entry slot based on live gate occupancy, and receive directions timed to that slot. Operators watch crowd density on a live dashboard.

  • Django REST Framework
  • React
  • PostgreSQL
  • Razorpay
  • AWS

PilotLMS

B.Tech thesis, 2022

A learning management system for IIT Kharagpur, with separate access for students, instructors and admins, course management, and dashboards showing how each course is going.

  • Python
  • Django

View code on GitHub

Neural turbulence modeling

M.Tech thesis, 2024

A neural network that predicts the pressure–strain correlation in turbulent flow, reaching an R² of 0.997.

  • Python
  • Deep learning

Writing

Mathematics for Competitive Programming and Data Structures

Mastering the Essentials · 2023 · 83 pages

A book I wrote for competitive programmers and students of data structures and algorithms. It covers the maths that keeps coming up in programming problems, including prime numbers, combinatorics, graph theory, trees, probability, geometry and linear algebra, with every idea worked through in C++.

Buy the ebook View on Google Books

Education

IIT Kharagpur

B.Tech and M.Tech dual degree

2019 – 2024

Outside class, I was Events Head at NAROES, leading a team of more than 30 to run the Samudramanthan fest, and twice led a 15-person team to a bronze medal at Open Soft, the institute’s inter-hall software competition.

Get in touch

I’m open to backend, platform and AI engineering roles. Email is the quickest way to reach me.

Email ayush.asax.saxena@gmail.com Message me on LinkedIn