Tech Stack

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Experience

My professional journey.

Application Support Engineer

The Co-operative Bank
Sep 2022 - Present
  • Monitored business-critical enterprise production systems in a regulated financial environment, analysing authentication, transaction, and fraud signals to detect anomalies and resolve 100+ incidents per month across online banking and backend services
  • Used observability dashboards and log analytics to identify recurring failure patterns and drive data-driven fixes, reducing mean resolution time by 30% and repeat incident rate by 25%
  • Managed account lifecycle and system state synchronization via ITSM tooling and runbook automation, ensuring data consistency across authentication, ML-driven fraud detection, and core banking systems
ITIL/ITSMITIL/ITSM
JiraJira
LinuxLinux
GitGit

Software Engineer

Peltarion
Nov 2020 - Jun 2022
  • Owned end-to-end development of a production-grade service using AWS CDK (TypeScript) and Java-based AWS Lambda functions, automating manual campaign management and scaling to 6M+ emails/day
  • Launched with AWS CloudWatch dashboards used daily by enterprise clients, cutting costs by $8K+ monthly and saving 80+ hours of manual work each week
  • Integrated with live systems processing 40M+ events/day by connecting AWS SNS and SQS to internal services and persisting artifacts in AWS S3, reducing campaign processing time by 23%
TypeScriptTypeScript
JavaJava
AWSAWS
Node.jsNode.js

Machine Learning Engineer Intern

THG Ingenuity
Apr 2020 - Sep 2020
  • Built a Python NLP pipeline with scikit-learn, spaCy, and NLTK, then productionized it as a Flask API with Redis caching, cutting processing time from 5 to 3 minutes across 1,200+ requirements per month
  • Engineered a BERT-based dependency extraction component for requirement lists, improving project planning efficiency by 37%
PythonPython
Node.jsNode.js
ExpressExpress

Software Engineer Intern

THG
Apr 2019 - Sep 2019
  • Built 30+ AWS Lambda functions and 15+ Step Function workflows using REST API integrations to improve reuse and reliability, reducing execution time by 65% and saving $1K per large-scale deployment
  • Built a Spring Boot app, containerized with Docker, and deployed on AWS EC2, serving 30+ stakeholders
AWSAWS
DockerDocker
Spring BootSpring Boot
JavaJava

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