Open to opportunities Coconut Creek, FL · Remote-friendly

Christopher
Beaulieu.

~/portfolio — zsh
§ 00

About

profile
N° 001 Christopher Beaulieu
Christopher Beaulieu
Senior Software Engineer
Coconut Creek, FL

I'm a Senior Software Engineer with 7+ years designing and operating scalable backend, data, and analytics systems in enterprise production environments. At Intel, I shipped platforms spanning production analytics services, ML-enabled data pipelines, GenAI-powered developer tooling, and CI/CD automation — with measurable outcomes attached to each.

I hold an M.S. in Computer Engineering from Georgia Tech. My core background is in C# and Python, though I'm comfortable across the full stack of a modern backend system, from distributed services to cloud infrastructure.

I lead small teams, mentor junior engineers, and treat shipping as a craft. I'm currently open to new opportunities and would love to connect if you're building something ambitious.

§ 01

Stack

grouped by what I build
01

Data pipelines

Large-scale ETL, feature engineering, statistical analysis, reliability modeling.

Python·Pandas·NumPy·SQL Server·PostgreSQL·Azure·Pydantic
02

ML / GenAI tooling

RAG systems, multi-LLM orchestration, production model integration, developer assistants.

Claude API·OpenAI API·Gemini API·RAG·Multi-provider failover·Python
03

Backend services

Distributed services, REST APIs, internal platforms, full-stack feature work.

C#·.NET / .NET Core·ASP.NET·Flask·HTMX·FastAPI·TypeScript
04

Cloud & ops

CI/CD ownership, container deployments, infrastructure for production analytics platforms.

Microsoft Azure·Docker·GitHub CI/CD·GitLab CI/CD·Linux·Windows Server·Artifactory
▸ also fluent in C++ · SQLite · BeautifulSoup4 · React · Vite · Playwright · SCRUM
§ 02

Experience

timeline · 2018 → 2025
2018
2026 ●
Mar 2020 — 2025
Δ 5 yrs
INTEL
Senior Data Analytics Software Engineer
  • 01.Led a team of engineers to build a production analytics platform, significantly improving signal identification and data workflows.
  • 02.Designed and operated large-scale ML-enabled data pipelines, including feature engineering and production model integration.
  • 03.Built an internal GenAI-powered developer assistance platform using RAG and LLMs, meaningfully improving code discovery and developer productivity.
  • 04.Owned CI/CD and deployment strategy across multiple applications, substantially reducing deployment time and production defect rates.
  • 05.Integrated SCRUM practices into team workflows and mentored junior engineers on development best practices.
C#.NETPythonAzureSQL ServerRAGLLMs
May 2018 — Mar 2020
Δ 2 yrs
INTEL
Software Engineer
  • 01.Developed analytics and statistical analysis applications supporting reliability modeling and failure-rate analysis.
  • 02.Improved analytical algorithms, achieving significant performance gains and reduced defect rates.
  • 03.Designed reusable application frameworks for backend data services and implemented CI/CD automation.
C#.NETPythonSQL Server
§ 03

Selected work

$ ls -la projects/
RSL Siege Manager Open source · Live

An open-source web app for managing Raid: Shadow Legends clan siege assignments — self-hostable anywhere Docker runs.

Drag-and-drop assignment board with an auto-fill algorithm, a real-time validation engine, PNG battle card generation via Playwright, and Discord DM notifications. Reference deployment runs on Azure Container Apps behind Discord auth.

FastAPIReactTypeScriptPostgreSQLDockerDiscordAzure
Job Matcher Solo · LLM pipeline

An LLM-powered job search pipeline that fetches listings from 9 sources, scores each description against your skills profile, and surfaces ranked results in a local web UI.

Multi-provider scoring (Claude, GPT-4, Gemini) with cost-per-call awareness and provider failover. Data stays local. One external contribution merged — a DB query optimization from a community fork.

PythonFlaskSQLiteHTMXPydanticMulti-LLMBS4
Support Triage Agent Hackathon · Judged

A terminal-based AI agent that triages support tickets across HackerRank, Claude, and Visa product corpora. Built solo for HackerRank Orchestrate (May 2026, 24 hrs); judged 65th of 12,885 participants across 1,349 submissions.

Nine-stage RAG pipeline — preprocess → safety → router → query expansion → classifier → retrieval → product-area resolution → abstain → generate — with per-stage unit tests, structured run tracing, and explicit abstention on out-of-corpus or high-risk tickets. Multi-provider LLM client with deterministic outputs.

PythonRAGMulti-LLMPydanticpytestAgentCLI
Qwen3.5 Quantization Study Research · Methodology

A 4-iteration empirical study quantizing Qwen3.5-0.8B for an agent on a CPU-only consumer-class envelope (8 threads, 16 GB).

Falsified the bandwidth-bound prediction at Iter-1, validated a refined dequant-overhead mechanism at Iter-2, and confirmed a novel KV-noise-as-attention-regularization hypothesis via a directional series. Recommended config: +18–27% decode, −16–31% memory, no quality regression.

Qwen3.5llama.cppGGUFQuantizationDockerCPU-onlyPython
More on GitHub Profile · @cbeaulieu-gt

Side projects, experiments, and open-source contributions live on my GitHub profile.

// note AI tooling (Claude Code, GPT, Cursor) was used to varying degrees across all of the above — for research, code generation, and validation. Architectural decisions, methodology, and shipped outcomes are mine.

§ 04

Contact

endpoint · always-on
Let's build
something.

I'm open to senior backend, data, and ML platform roles. Inbox is always on.

POST /hello → christopher_m_beaulieu@outlook.com