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TAM-DS/README.md

Tracy Manning

Staff-Level AI Systems Engineer Production MLOps • Multi-Cloud Infrastructure • Agentic AI • Austin, TX

I design and operate production AI systems — the kind that keep working when assumptions fail, costs spike, or something breaks at 2am.

My work sits at the intersection of machine learning, infrastructure, and systems design: deploying agentic AI, building cloud-agnostic platforms, and turning fragile prototypes into systems teams can trust in production.

I focus on how systems behave after launch — not just how they look on a diagram. I care as much about how decisions land as whether they’re technically correct.

What I Build

When Python becomes the bottleneck, I drop down to C++ and CUDA to meet latency, throughput, or cost constraints.

Production AI & MLOps

  • Agentic AI and RAG systems designed for reliability, observability, and security

  • Retrieval and vector database layers built to fail safely

  • Model serving, inference optimization, and real-time pipelines

  • Linux-native ML infrastructure (production runs on kernels, not notebooks)

AI Platform & Infrastructure

  • Multi-cloud architectures across AWS, GCP, and Databricks

  • Kubernetes-first platforms with Terraform-based IaC

  • Secure networking, identity, and isolation for AI workloads

  • Systems designed to scale without vendor lock-in

Data Engineering at Scale

  • Petabyte-scale data pipelines (Bronze → Silver → Gold)

  • Streaming and batch systems optimized for cost and throughput

  • Architectures that reduce spend by design, not after the bill arrives

Platforms & Credentials

  • AWS Solutions Architect – Professional (SAP)

  • Google Cloud Professional Machine Learning Engineer

  • Databricks Machine Learning Professional

Tools (When They’re the Right Tool)

  • Python • SQL • PyTorch
  • C++ • CUDA (performance-critical paths)
  • Kubernetes • Terraform • Docker
  • AWS • GCP • Databricks
  • Linux (kernel → networking → performance)

Harvard alum.

  • Builder of systems that must work in production.

Featured Projects

In 2030 your data center orbits 550km above Earth. No technicians. No human latency. Here’s exactly how attackers win—and how we build systems that survive autonomously.

20-dashboard series exploring Texas as the emerging capital of AI infrastructure: grid power → megawatts → teraflops → orbital compute.

Signal-based trading system with full backtesting framework.

Experimental quantum circuits in Qiskit exploring future-secure and future-ready architectures.

Tableau dashboards that push the boundaries of data storytelling.

Technical Stack

Cloud
AWS GCP Azure Databricks

Languages & Data
Python SQL Apache Spark

ML Frameworks
PyTorch TensorFlow MLflow

Infra & DevOps
Linux Kubernetes Docker Terraform

Connect

🌐 Portfolio • 💼 LinkedIn • 🐦 X • 📲 Join my WhatsApp Channel for exclusive PDFs, checklists, and weekly orbital AI insights:
https://whatsapp.com/channel/0029Vb6rVBD29757lPbMat3P

Shipping production systems that don’t wake you at 2am. Austin, Texas.



Streak Stats

tam-ds

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  1. Quant11 Quant11 Public

    This 30-line algorithm implements quantum teleportation - the foundation of quantum internet

    1

  2. Texas-Energy-Data-Pulse Texas-Energy-Data-Pulse Public

    Each dashboard in this repository visualizes a different dimension of transformation: from megawatts to teraflops, from on-prem to orbit, from human oversight to autonomous systems.

    1

  3. OWASP-LLM-Attack-Surface-2025-Edition- OWASP-LLM-Attack-Surface-2025-Edition- Public

    This dashboard maps the full OWASP LLM vulnerability landscape, showing where risks originate, how they propagate across the AI stack, and which controls matter most for LLM deployments in producti…

    1

  4. RAG-Attack-Surface-Propagation-Map-2025-Edition- RAG-Attack-Surface-Propagation-Map-2025-Edition- Public

    A system-level analysis of how Retrieval-Augmented Generation (RAG) pipelines break — and how failures propagate.

    1

  5. The-Physics-Constraint-2030 The-Physics-Constraint-2030 Public

    By 2030, light-speed delay will be faster than human decision cycles.

  6. Orbital-AI-Security-Analysis-Series Orbital-AI-Security-Analysis-Series Public

    Comprehensive framework analyzing AI security from terrestrial to orbital deployments

    1