Devin Vitone

About Devin Vitone

Staff-level engineer with 10+ years of experience building robust machine learning platforms, internal developer platforms, and cloud-native systems. I specialize in enabling high-scale data and AI workloads with a focus on developer velocity, infrastructure resilience, and operational simplicity. I bring deep technical expertise and depth across a wide range of domains as as as the ability to effectively communicate ideas and concepts with both technical and non-technical audiences.At Koch Industries, I’ve led efforts to design and scale a secure software and ML solutions introducing many of the DevOps and Software Engineering pactices and tools now used in our orginization. I was an early member of the team responsible for developing and delivering our ChatGPT-style internal LLM system used across the enterprise, while also building a Kubernetes-based IDP (Internal Developer Platform) with ArgoCD, Crossplane, and Terraform. I thrive in the space between ML, infrastructure, developer experience, software engineering and bring a product-focused mindset to each of these areas.Key interests: LLMOps, Generative AI, Application Development, Platform Engineering, GitOps, DevEx, Infra at ScaleTools I love: Kubernetes, Terraform, ArgoCD, Crossplane, AWS, Datadog, Python, Dask

Experience

1. Senior Machine Learning Engineer

   Koch

   Sep 2020 — Present

   Led the design and implementation of scalable ML infrastructure and developer enablement platforms for Koch’s Data & Analytics organization, supporting both traditional data science workflows and emerging Generative AI use cases.Early key team member in developing an internal ChatGPT-style system used across the enterprise to securely access internal documentation and systems via natural language, dramatically improving engineering and research productivity.Built a Kubernetes-based Internal Developer Platform (IDP) using Crossplane, ArgoCD, and Terraform, enabling self-service deployments and accelerating onboarding for multiple engineering teams.Developed core LLMOps capabilities, including token usage tracking, sandboxed execution, agent plugin interfaces, and identity-aware access patterns.Championed adoption of GitOps and Infrastructure-as-Code (IaC) practices; defined standards, authored reusable templates, and mentored engineers across teams.Integrated observability and performance monitoring with Datadog and service exposure via Kong API Gateway to ensure operational excellence.Collaborated closely with security and architecture stakeholders to align scalable AI systems with enterprise guardrails and compliance policies.Served as a trusted advisor and hands-on contributor across ML, platform, and data engineering initiatives, operating at a Staff+ level of technical ownership.Technologies: Kubernetes, Terraform, Crossplane, ArgoCD, AWS, Python, Dask, Scikit-learn, TensorFlow, Datadog, Kong, Generative AI, LLMOps, GitOps, CI/CD, OR-Tools

Education

• The University of Texas

  Bachelors of Science, Electrical Engineering

  2004 — 2009

• The University of Texas at Austin

  B.S., Electrical Engineering

  2004 — 2009

Skills

• Field-Programmable Gate Arrays (Fpga)
• Eclipse
• Digital Signal Processing
• Systems Engineering
• Semiconductors
• Shell Scripting
• Labview
• Testing
• Apache
• Git
• Matlab
• C++
• Unix
• Hardware
• Java
• Ruby
• Simics
• Verilog
• Perl
• Embedded Systems
• Tcp/Ip
• Software Engineering
• Networking
• C
• Hardware Architecture
• Vhdl
• Agile Methodologies
• Emulation
• Web Applications
• Linux
• C
• Programming
• Microsoft Office
• Node.js
• Mobile Devices
• Fpga
• Embedded Software
• Ruby on Rails
• Debugging
• Software Development