Dmitrii Kharlamov

Senior Full Stack Engineer @Maeve Ai

Berlin, DE
MOBILE NUMBERS
+91 *********19

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WORK HISTORY

Oct 2025 — Present

Senior Full Stack Engineer @Maeve Ai

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Berlin, DE

EDUCATION

2020 — 2022

MITx Courses

Micromasters Candidate, Data, Economics and Development Policy

2000 — 2002

Southern Federal University (former Rostov State University)

Candidate, Computer Science

2021 — 2022

Institute of Trading and Portfolio Management

Professional Trading Masterclass

SKILLS

Css3DjangoJavaRubyHtmlXmlAjaxIosUser Interface ProgrammingJavascriptHtml 5AssemblaRuby on RailsPhpmyadminRspecPhpZepto.jsJquery UIJqueryIllustratorFlashStart-UpsJava Enterprise EditionFlexSouthUser InterfaceWeb DevelopmentBackbone.jsPhotoshopSubversionMysqlObjective-CGithubProgrammingProject ManagementWeb ServicesJsonMobile ApplicationsCssActionscript

ABOUT DMITRII KHARLAMOV

Five times I\'ve joined a founding team, built the core product, and that workdirectly led to a fundraise or acquisition. I co-founded four startups: onebootstrapped, three raised $385M total. One failed, one is scaling in a $850B+market, and two were acquired — one by Google.I approach problems from first principles. I am a spatial and systems thinker, astrategist, technocrat, and a hacker. I am interested in electronics, CPUarchitecture, memory models, low-latency systems, database design, backendsystems, and frontend UX. I am a multidisciplinary specialist because I believeI can architect solutions only by understanding the full context — from cachelines to user interfaces.Across these systems I have consistently optimised for latency and throughput:reduced restaurant filtering from 1–2s to <100ms by redesigning data retrievalaround MongoDB limitations; increased single-server capacity from 100 to 2,500requests/second (potential r/s) through WSGI, caching, and databasetuning; cut ETL and data warehouse refresh runtime by 50%(9 hours to 4.5hours); replaced a third-party analytics layer with Cube.js, reducing table loadtime from 5s to <500ms (50ms cached) and 54 API requests down to 3; achieved15% smaller video file sizes at higher audio-visual quality than YouTube HD circa2012 through custom FFMPEG transcoding pipelines. Built an ML-based predictiverouting system that forecast driver positions five deliveries ahead.I identify industry problems before they become obvious (currently: hiring isfundamentally broken and complexity is killing developer productivity). Ichallenge conventional wisdom not to be contrarian, but because I have thetechnical foundation to evaluate claims independently.I am battle-tested, grounded, and capable of leading in uncertain, high-stakesenvironments. Currently building low-latency systems in C++ and Rust — includinga matching engine and a market data feed parser.

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