Chris Cordaro Applied AI · ML systems · Production

Raleigh, NC

Chris Cordaro, AI and ML engineer.

I build AI software that turns a day of federal research into minutes. For twelve years I’ve built data and ML systems for the Department of Defense, FEMA and the Military Health System.

Download resume See the work →

What the software gives back

Each pair of bars is drawn to scale.

  1. Researching a federal solicitation

    Before about 2 hours
    With Scout under 2 minutes

  2. Writing a 15-page competitive intelligence report

    Before 8+ hours
    With Scout about 6 minutes

  3. Manual workforce analysis at the DoD Inspector General

    Before baseline
    After 60% less time

Selected work

Four projects, from a product I designed and built alone to platforms I led teams to deliver.

  1. Scout

    A production SaaS that monitors federal solicitations

    I was the sole architect, from schema to ship. Scout aggregates solicitations from multiple sources, removes duplicates in four tiers, and scores each one with AI. More than 20 people use it across 50,000+ active solicitations.

    • Research copilot

      Classifies the question, retrieves with full-text and vector search together, and streams an answer from an LLM.

    • Competitive intelligence pipeline

      Role-specialized agents work in four phases across SAM.gov, USASpending, FPDS and SBA, reporting live progress as they go.

    • Agent tooling

      14 agent personas with persistent memory, plus 30+ MCP servers, skills and plugins with 150+ installs across three CLIs.

  2. Workforce allocation platform

    DoD Office of Inspector General

    I led the build of a platform that forecasts demand with LSTM networks, scores attrition risk with XGBoost, allocates staff under constraints with genetic algorithms, and classifies positions and skills with BERT. Program offices read the results in self-service dashboards.

  3. UkraineOversight.gov

    Knowesis for the DoD Inspector General

    I designed and delivered the public, interactive Tableau dashboards behind the site.

  4. Self-service data platform

    Knowesis for the DoD Inspector General

    I directed a 15-person team of data scientists, engineers and BI analysts through a migration to a modern data stack over 40+ sprints, and founded a Data Science Center of Excellence along the way.

How I build

  1. Understand the data and the user first

    Find out what decision the user is making and whether the data can support it before writing code.

  2. Prototype the risky part

    Build whatever is most likely to fail first, usually retrieval quality, model accuracy, or throughput.

  3. Ship in increments, with the plumbing

    Tests, CI, containers, and observability from the first increment, and I stay in the code.

  4. Measure adoption

    It’s finished when people use it and a number moves, such as hours saved per task.

Career

  1. 2025 to now

    Knowesis, Raleigh

    AI Engineering Lead and Program Manager

    Building Scout and leading a 16-person team supporting health readiness policy and oversight across the Military Health System.

  2. 2024 to 2025

    DoD Office of Inspector General, Alexandria

    Enterprise Business Innovation Manager

    Led the workforce platform and the agency’s move from manual reporting to self-service analytics.

  3. 2019 to 2024

    Knowesis for the DoD Inspector General, Alexandria

    Technical Lead and Program Manager, Data Platform

    Ran the data-stack migration and UkraineOversight.gov. Received the Glenn/Roth Award for Exemplary Service.

  4. 2018 to 2019

    Knowesis for FEMA and the Defense Health Agency, Washington

    Solution Architect

    Delivered a disaster-recovery system for iOS, Android and web on AWS, and a records system that cut manual workload 45%.

  5. 2013 to 2018

    Atkins for FEMA, Columbia

    Data Manager

    Built the data systems behind FEMA funding coordination for more than $300M across 22 counties.

B.S. in Management Information Systems from UNC Charlotte. PMI Agile Certified Practitioner, Tableau Certified Associate, HarvardX Data Science Professional Certificate and DataWalk Technical Professional.

Download resume (PDF) →

Toolkit

  1. Generative AI

    Retrieval-augmented generation with hybrid retrieval and pgvector, multi-agent orchestration, MCP, the Claude and Gemini APIs, LangChain and LangGraph.

  2. Machine learning

    TensorFlow, scikit-learn, XGBoost, LSTM, BERT, genetic algorithms, forecasting, evaluation and validation.

  3. Languages and frameworks

    Python, TypeScript, SQL, FastAPI, React, Next.js, Node.js and R.

  4. Infrastructure and testing

    Docker, Kubernetes, Cloudflare, AWS, Azure, GCP, GitHub Actions, pytest, Vitest, Ruff, mypy and Semgrep.

  5. Data and BI

    PostgreSQL, SQLAlchemy, Drizzle, SQL Server, Tableau, Power BI, Spark and Databricks.

  6. Federal domain

    FAR and DFARS, FedRAMP, CMMC, Zero Trust, OTA acquisition, SAM.gov and Shipley methodology.

About

Chris Cordaro

Most of my work starts with a question someone can’t yet answer from their data. I work out which numbers matter and build the software that produces them. I also build on my own time: this site, a daily AI briefing that researches, writes, and publishes itself, and agent tools that other engineers install.

Read the daily briefing →Agent tools on GitHub →

Federal and defense

Active SECRET clearance. Twelve years in DoD, DHA, and FEMA environments. Fluent in FedRAMP, CMMC, Zero Trust, FAR/DFARS, and OTA acquisition.

Contact

Have a slow process that should be fast?

I like hearing about hard data and AI problems, especially in government. Email is the quickest way to reach me.

[email protected]
Download resume
View LinkedIn profileGitHub