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Andrei NeagoeAN
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Andrei Neagoe

@andreineagoe

Full-stack software engineer at Framestore who delivered its Public Links service and built Garzoni, an AI-powered financial learning platform.

Romania
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At Framestore, I develop internal applications the studio relies on, including review, scheduling, and messaging tools. I delivered the Public Links service end to end, with a React front end and serverless AWS back end; caching cut repeat load times from 348 ms to 21 ms.

I improved the service’s average response time from 3.3 seconds to 290 ms and set up its infrastructure as code in Terraform. I also led development of Framecast, implementing live shared cursors and drawing tools with WebRTC.

I’m the founder and sole engineer behind Garzoni, an AI-powered financial learning platform live on web, iOS, and Android. I built its Django and PostgreSQL API, React web app, and React Native mobile app, and developed an AI finance tutor that uses course-content search and voice responses.

I operate Garzoni in production with Docker, Railway, and Vercel, with automated database backups and CI checks for vulnerable dependencies and leaked secrets. Earlier, at Brixton Radio, I wrote scripts to keep social media analytics in sync and helped automate the transfer of audience statistics to Google Sheets.

Experience

Work history, roles, and key accomplishments

Education

Degrees, certifications, and relevant coursework

Queen Mary University of London logoQL

Queen Mary University of London

Bachelor of Science (Hons), Computer Science

2022 - 2025

Grade: 2:1

Activities and societies: Led team projects from requirements to final demo; ranked in the top 10% in key technical modules.

BSc (Hons) Computer Science with 2:1, BCS-accredited, from the School of Electronic Engineering and Computer Science. Coursework included software engineering, databases, web development, and neural networks.

Royal Academy of Engineering logoRE

Royal Academy of Engineering

Masterclass, Graduate Engineering Engagement Programme

2023 - 2024

Masterclasses at the Royal Academy of Engineering: eight months on the Graduate Engineering Engagement Programme, covering networking, public speaking, personal branding and taking research through to commercialisation.

FR

Framestore

Internal Training, Machine Learning and Web Development

Internal training at Framestore: ML at Framestore, a four-day programme on model building, MLOps, data provenance, diffusion models and LLMs; and the Web Development Group, 30+ sessions on the studio's web stack.

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