Hello, I'm

Max Fortner

Software engineer and Computer Science student at Dartmouth College, currently interning at Amazon Web Services. I build full-stack tools, AI-powered applications, and scalable systems.

Greek column

About

I'm a double-major in Computer Science and Classics at Dartmouth College with a 3.7 GPA. I love solving complex problems across the full stack, from optimizing SQL queries at scale to building AI orchestration layers that transform raw documents into interactive learning experiences.

Currently, I'm a software engineering intern on the AWS IVS real-time streaming team in San Francisco, where I'm designing and implementing a max-min fair rate limiter in Go. Previously, I developed internal tools at Tuck Advisors to support M&A deal sourcing and data analysis, built a Ukrainian language learning platform at Kleo used across 30+ countries, optimized production databases at Fischer Homes, and taught C programming at Dartmouth.

When I'm not coding, you'll find me reading ancient Greek, hiking in the White Mountains, playing the drums, or rock climbing.

Technologies

PythonTypeScriptJavaScriptReactNext.jsNode.jsFastAPISQLPostgreSQLDockerGitLinuxBashTailwind CSSREST APIsWebSocketsSupabaseRedisOAuth / JWTOpenAI APIAnthropic APIGoogle Gemini APILLM OrchestrationRAGVector DatabasesChromaDBMachine LearningCI/CDGitHub ActionsAWSGCPSystem DesignCSwift

Experience

Sep — Nov 2026

Software Development Engineer Intern · Amazon Web Services

San Francisco, CA

  • Work on the real-time streaming (RTX) team within Amazon Interactive Video Service (IVS), which powers low-latency live video streaming and real-time interactive experiences at scale
  • Design and implement a max-min fair scheduling rate limiter in Go, allocating capacity fairly across competing clients under bursty load so no single client starves others
  • Projected to reduce delayed requests by 75% in thundering herd and high-traffic scenarios
GoAWSLive Video StreamingDistributed SystemsRate Limiting

Jan — May 2026

Software Engineer · Tuck Advisors

Hanover, NH

  • Developed internal full-stack tools to support M&A deal sourcing, diligence workflows, and data analysis
  • Built backend services and automation to process structured and unstructured data used by advisors
  • Designed and maintained APIs and internal dashboards to improve data accessibility and decision-making
TypeScriptReactNext.jsPythonREST APIs

Sep — Dec 2025

Teaching Assistant · Dartmouth College

Hanover, NH

  • Supported students in C programming, UNIX tooling, debugging, and software testing practices
  • Reviewed and graded programming assignments with emphasis on correctness and code quality
  • Provided guidance on debugging strategies and writing maintainable systems-level code
CUNIXGitCode Review

Jun — Aug 2024

Database Administration Intern · Fischer Homes

Cincinnati, OH

  • Optimized SQL queries and indexing strategies, reducing report generation latency by 50% for 100+ users
  • Diagnosed and resolved 50+ production database performance issues, improving reliability and uptime
  • Built automated Power BI dashboards backed by SQL data models for executive reporting
SQLPower BIDatabase OptimizationETL

Jan 2022 — Jan 2023

Software Engineer · Kleo

Cincinnati, OH

  • Developed a Ukrainian language learning course used by learners across 30+ countries and 40 U.S. states
  • Built mobile-first interfaces in Swift and implemented progress tracking for structured language acquisition
SwiftiOSMobile Development

Projects

Interactive Greek & Latin Reader

Classics Reader

An interactive reader for whole Greek and Latin texts — original and English aligned clause by clause, every word a clickable token with lemma, parsing, gloss and a syntax note, plus a parse trainer, form drills, generated practice questions and Anki decks. Built for an advanced Greek course at Dartmouth and kept online for other students. The TypeScript engine is verified by equivalence against its hand-written predecessor, running the original browser code headlessly over all 326 segments; readings are prepared by an AI agent against a published spec, and every token carries a provenance mark so generated analysis never presents itself as checked analysis.

TypeScriptNext.jsReactPythonMorpheusPerseus TEIAnki

QSS 20 Research Project

Which rural places move kids up?

Tract-level analysis of the Opportunity Insights Opportunity Atlas asking what separates rural Census tracts with above-average upward mobility from otherwise similar rural tracts. Standardized OLS over 71,958 tracts with commuting-zone fixed effects and CZ-clustered standard errors, plus a precision screen and a dense-urban comparison. Single-parent household share is the largest adjusted association; local job, commute, and employment measures are indistinguishable from zero.

PythonpandasstatsmodelsmatplotlibJupyterOLS / Fixed Effects

Darts Scoring Software

FusionTally

Darts scoring software with configurable handicap rules applied dynamically at request time, a MongoDB-backed data model for players/matches/leagues/tournaments, and normalized stats & season analytics exposed through a REST/JSON API. Includes a touch-friendly React Native UI optimized for real-time scoring in live venues.

React NativeMongoDBREST/JSONAnalyticsMobile UI

AI-Powered Course Generator

Luminate

Full-stack PDF-to-course pipeline using PyMuPDF and Azure Document Intelligence for OCR, chunking documents into structured content, then generating quizzes, flashcards, and course sections via a multi-LLM orchestration layer (GPT-4, Claude, Gemini) optimized by task and cost. Streams real-time generation with SSE in a Next.js 15 frontend backed by Supabase auth and ChromaDB vector storage.

Next.js 15SSESupabase AuthChromaDBAzure Document IntelligencePyMuPDFOpenAI/Anthropic/Google

Contact

Interested in working together or just want to say hello? I'd love to hear from you.