KALPIT SHUKLA · Senior Java Engineer · Electronic Trading · London
Available Immediately
Kalpit Shukla
Kalpit Shukla
16 Years · Citi · MarketAxess
Senior Java contractor. Electronic trading depth. No ramp-up required.


Java 21 FIX 4.4/5.0 Spring Boot Kafka kdb+/q React Angular Oracle Redis Docker LangChain4j AWS AI & ML Python(scripting, data analysis, ML)

Fixed Income RFQ Equities FX Algo Trading Low Latency Payments Post Trade MiFID II

⬡ Kaltech
⬡ MarketAxess
⬡ Citibank
⬡ Earlier
⬡ About
Kaltech Software Ltd
Dec 2025 – Present
Contract
Equity Signal Engine
Java 21 · Spring Boot 3 · Virtual Threads · LangChain4j · ta4j · React · REST APIs
  • Built a real-time signal computation engine scanning the S&P 500 universe — multi-provider market data integration with configurable abstracted REST client layer.
  • Technical indicator computation (RSI, MACD via ta4j) for pre-trade signal generation across 500+ instruments simultaneously.
  • Virtual-thread executor service managing ~500 concurrent instrument fetches with rate-limit-aware scheduling using scheduleAtFixedRate batching — no CountDownLatch overhead, deterministic throughput under provider constraints.
  • Sub-100ms signal generation latency across 500 concurrent instruments.
  • LangChain4j LLM integration for AI-powered signal rationale generation using Claude API via AWS Bedrock.
  • React frontend with multi-dimensional scoring heatmap (T/F/C/B/G/E/S/M dimensions) powered by Nivo charts.
MarketAxess
Mar 2020 – Nov 2025 · Contract then Permanent (Jul 2022)
Senior Software Engineer — Front Office Fixed Income Bond Trading
Bondlink — Fixed Income RFQ Trading Platform
Java 11-21 · Spring · FIX Protocol · IBM MQ · JMS · Kafka · Oracle · Shell Script
  • Delivered key enhancements for UK and Europe Fixed Income market segments — UK Gilts, European Credit, EM bonds.
  • Contributed across multiple trading flows: RFQ Open Trading, Disclosed, List, Crossing, AXE, Portfolio, and IOI — price/spread protocols for One Step, Spot, and Phone Trade execution paths.
  • Covered full trade lifecycle from RFQ execution through to post-trade booking confirmation and settlement instruction generation via FIX — T+1/T+2 cycles.
  • Modernisation of legacy Bondlink components to JDK 21.
  • Owned production release cycle for Bondlink UK/EU segments — release coordination, deployment verification, post-release monitoring.
  • Used Claude via AWS Bedrock to document FIX workflows — test coverage from under 10% to 45%, reducing Checkmarx security vulnerabilities.
REMS — Real-Time Exception Management Surveillance
React · Java 21 · Spring Boot · REST APIs · Redis · Docker · Kubernetes · AWS
  • Designed REMS post-trade exception management platform — trade break identification, failed settlement resolution, allocation updates.
  • ORK-to-ARM record conversion and FCA submission covering MiFID II RTS22 transaction reporting, RTS23 reference data, RTS24 order record keeping.
  • React/AG Grid dashboard with server-side rendering, Spring Boot REST with Spring Cloud Circuit Breaker, Spring Data on AWS RDS.
Citibank
Feb 2011 – Jun 2018 · 7 Years
Senior Core Java Developer (AVP) — Front Office Equities & FX
CITI SMART — Algorithmic Trading Engine
Java 8 · Spring 3.5 · LMAX Disruptor · FIX 4.4 · TIBCO EMS · kdb+ · Bloomberg · Reuters · Unix
  • Engineered low-latency performance improvements — replaced synchronized blocks with lock-free data structures and java.util.concurrent primitives (ConcurrentHashMap, Atomic classes, tryLock with timeout) eliminating lock contention.
  • Consumed LMAX Disruptor v3 ring buffer within the CFore→SMART order pipeline, processing inbound FIX orders via BusySpinWaitStrategy on a dedicated isolated CPU core.
  • Optimised critical path execution by identifying and removing contention hotspots in order routing and fill processing — reduced thread-blocking on shared state.
  • Profiled JVM heap allocation and GC behaviour using Java Flight Recorder and async-profiler — applied object pooling to reduce GC pressure on critical execution path.
  • Engine consumed orders from CFORE and routed to market using Bloomberg and Reuters real-time market data via CitiMatch internal dark pool.
Total Touch / Liquifi / CitiMatch — Dark Pool
Java · FIX 4.4 · TIBCO EMS
  • Delivered IOI features for Total Touch — the in-house liquidity provider and internal crossing engine for Citi Equity business.
  • CitiMatch served as the integrated dark pool execution venue and test ecosystem for CITI SMART.
FX Options Pricing
Java · kdb+/q · Bloomberg · Reuters · TIBCO EMS
  • Implemented FX options pricing data services — extended data models with options-specific attributes (strike price, expiry date, option type, Greeks: Delta, Gamma, Theta).
  • Integrated real-time spot rates from Bloomberg and Reuters, published enriched pricing data to front-office trading systems via TIBCO EMS.
  • Updated kdb+ schema for FX options data with efficient partitioning and indexing for real-time analysis.
Earlier Contracts & Roles
Jun 2007 – Feb 2011 / Jul 2018 – Mar 2020
Java Developer / Lead / Application Developer
JAJA Finance — Microservices Migration
Java · Spring Boot · Kafka · AWS · ISO 8583 · ISO 20022
  • Led migration from monolithic to event-driven microservices for a challenger bank payments platform.
  • Implemented ISO 8583, ISO 20022 message translation layer and real-time payment processing services.
TP ICAP — Execution Report Distribution
Java · Spring Boot · Solace · Hazelcast · AWS S3
  • Two-node distributed execution report aggregation service — deduplication by orderId/tradeId, zip generation, S3 upload, automatic failover to secondary node.
10xBanking / Infosys — FX Rate Processing
Java · Spring Boot · AWS · Docker · Kubernetes · Grafana
  • Real-time FX rate ISO 20022 message processing services on AWS with zero-downtime Kubernetes deployment.
3i-Infotech — Credit Suisse / ABSA Barclays
Java · Spring · Oracle
  • Extended KASTLE Factoring platform for Credit Suisse and ABSA/Barclays — onsite engagement at Credit Suisse, Zurich.
About Kalpit
Quiet Leader · Strategist · Builder

I am a Senior Software Engineer with 16 years of front-office electronic trading experience across Equities, Fixed Income and FX.

My approach to complex problems comes from a principle I have internalised over years of delivery: difficulty exists only when the unknown is unidentified. When facing a hard technical challenge I decompose it ruthlessly -- breaking it into subtasks, going three levels deep on each unknown, writing down what is missing and what the alternatives are. What looks intimidating on the surface becomes a sequence of solvable steps. I applied this instinct to a greenfield FCA regulatory reporting system that I delivered end to end in three weeks -- a project estimated at $1 million by a Big4 firm. I applied it again to lock-free concurrency in a live algorithmic trading engine processing institutional order flow at Citibank. And I apply it every time.

I apply the same rigour to testing as I do to delivery -- identifying edge cases, stress points, and failure modes before they reach production. A bug found in development costs minutes. The same bug in a live trading system costs far more.

One delivery I am particularly proud of at MarketAxess was the Bulk Upload feature on the Bondlink platform -- a piece of functionality that had been untouched for years. I took it on, understood the full scope across dozens of different RFQ flows, and delivered it end to end including testing in under a month. Before this, the business had to investigate and fix trades for clients and dealers one at a time -- an exhausting manual process that became critical under heavy load at month end or during high-volume periods. After delivery, operations could add multiple trade flows in a single screen -- selecting client, dealer, quantity, price, venue, RFQ type (Open Trading, Disclosed, Anonymous, Crossing) and more -- execute everything in a single click and receive execution reports for each trade individually.

My focus has never been purely on writing code -- it is on understanding what the business needs and delivering value through the right technical solution. I believe the best engineers ask questions, challenge assumptions, and provide feedback early -- not just sit and execute tickets. I have always chosen growth over comfort. When an environment stopped challenging me technically, I found one that did.

I lead quietly. Not through volume or politics but through delivery and technical depth. My colleagues describe me as hardworking, helpful and focused. I work best in teams where the energy goes into solving problems and raising the standard collectively.

Outside of work I follow financial markets -- equities, futures, options, commodities like oil and gold, and real estate. I find it interesting how these are all connected -- a move in oil affects inflation, inflation affects bond yields, bond yields affect equities. Having this awareness helps when building systems that operate in these markets every day.

Kaltech Software Ltd

The engine was not a tutorial project. It manages ~500 concurrent instrument fetches using Java 21 virtual threads, with rate-limit-aware scheduling that ensures deterministic throughput without CountDownLatch overhead. The data ingestion layer abstracts multiple market data providers behind a configurable REST client — meaning swapping providers requires zero code changes.

I integrated LangChain4j and the Claude API to generate AI-powered signal rationale — giving each technical indicator signal a human-readable explanation. This was not a demo. It runs, it produces output, and it informed my own investment decisions.

The React frontend renders a multi-dimensional scoring heatmap across Technical, Fundamental, Catalyst, Behavioural, Growth, ESG, Sentiment and Momentum dimensions.

KS
Hello. I'm Kalpit — ask me anything about my experience, the role shown, or my availability.
just now