Backend Engineer · Data Engineer · Delhi, India

Chetan Kumar Tyagi

5+ years engineering trading infrastructure, distributed data pipelines, and multi-agent LLM systems. Currently at QuantInsti building the data backbone for Blueshift — a live algorithmic trading platform.

View workResumeiamcktyagi@gmail.com

5+

Years of experience

3

Companies

65%

Pipeline speed-up

14+

Broker integrations

Experience

Jul 2024 – Present

Mumbai, India

Software Development Engineer

QuantInsti Quantitative Learning

  • –Built production-grade data ingestion pipelines for OHLC, tick, and fundamental data across equities, futures, options, and indices on the Blueshift platform.
  • –Performance-tuned the options data ingestion pipeline end-to-end — reducing ingestion time from ~90 min to 25–30 min (65%+ improvement) through parallelisation and profiling-driven refactoring.

Oct 2023 – Jun 2024

Thane, India

Senior Software Engineer

Neam Caps (sharpely / finpeg)

  • –Profiled and optimised database queries and legacy systems — achieving 80% faster query results and 50% reduction in resource usage.
  • –Conducted large-scale backtesting for equity trading strategies using QuantConnect Lean (Python); collaborated with market researchers to surface actionable signals.

Apr 2021 – Oct 2023

Noida, India

Software Engineer

WealthWisers Technologies

  • –Engineered TradeTez — a multi-broker, multi-account trading backend supporting NSE and NYSE markets across IIFL, SMC, Zerodha, and 5Paisa.
  • –Built end-to-end trading bots covering backtesting, optimisation, and live execution using broker APIs; handled concurrent multi-account order routing reliably.

Selected Work

AI / LLM2024 – Present

Multi-Agent Trading Research System

Multi-agent orchestration system using Google Vertex AI (Gemini) and Claude as intelligent orchestrators — with DAG-based task routing and fallback model chains applied to trading strategy research and signal analysis.

PythonClaude APIGeminiMulti-agent
Trading Systems2022 – 2024

Automated Scalper

Fully automated trading engine with three decoupled modules — Data Adapter, Position Manager, and Executioner — using Kotak Neo APIs and AMQP-based messaging for distributed real-time execution.

PythonAMQPRabbitMQRedis
Backend2021 – 2023

TradeTez Backend

Multi-broker unified execution backend supporting NSE and NYSE markets across IIFL, SMC, Zerodha, and 5Paisa — with asynchronous APIs, high-speed data routing, and webhook-triggered order execution.

PythonDjangoRedisWebSockets
All projects →

Technical Skills

Core Languages

Python (expert), Rust, SQL, Bash

AI & LLM

Multi-agent orchestration, Claude API, Gemini / Vertex AI, OpenAI API, Ollama, MCP (server + client), Prompt engineering

Data Engineering

Airflow, PySpark (Core / SQL / Streaming), Pandas, Polars, Parquet, Snowflake, Hive / HDFS, DuckDB

Backend

FastAPI, Django, Flask, WebSockets, Socket.IO, AsyncIO, AMQP, MQTT

Databases

PostgreSQL, MySQL, MongoDB, Redis, SQLite, CrateDB

Infrastructure

AWS (EC2, EKS, S3, Lambda, RDS, Athena, Glue, SQS), Docker, Git / CI/CD, Ubuntu / Linux

Trading & Quant

Broker API integration, Options pricing (SABR, Black-Scholes), Event-driven execution, Backtesting, Tick / OHLC data