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.
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
-
AWS Solutions Architect – Professional (SAP)
-
Google Cloud Professional Machine Learning Engineer
-
Databricks Machine Learning Professional
- Python • SQL • PyTorch
- C++ • CUDA (performance-critical paths)
- Kubernetes • Terraform • Docker
- AWS • GCP • Databricks
- Linux (kernel → networking → performance)
- Builder of systems that must work in production.
Production-grade system designs that survive real constraints — not just whiteboard sketches.
8 deep dives covering:
• End-to-end MLOps pipelines
• Secure LLM systems (from first principles)
• Multi-cloud agentic AI deployment
• Kubernetes ML workloads
• Orbital autonomous control
• Medallion data lakehouses
• RAG at scale
• Data engineering foundations
Built to teach how systems behave under pressure — latency, drift, security, and 2am failures.
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.
Experimental quantum circuits in Qiskit exploring future-secure and future-ready architectures.
Tableau dashboards that push the boundaries of data storytelling.
Cloud
Languages & Data
ML Frameworks
Infra & DevOps
🌐 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.