Josef Doornink
Site Reliability Engineer | AI Infrastructure & MLOps
A creative problem-solver who creates solutions where none exist, I build the infrastructure that scales research into reality. Few production engineers have published 10 peer-reviewed papers, earned 2 US patents, won a major design award, and shipped FDA-cleared hardware. That discipline now drives 10+ years of SRE and AI infrastructure work (CKS/CKA certified), bridging mathematical rigor and system integrity at scale — currently designing autonomous Agentic SRE pipelines that leverage LLMs for root-cause analysis.
Featured Projects
K8gentS
What happens when you deploy a non-deterministic reasoning engine in a system that requires guarantees? K8gentS is an autonomous Kubernetes RCA agent built around that question. It routes cluster failures through Gemini-powered analysis, gates remediation behind both a human approval and an OPA Gatekeeper admission policy, and exposes diagnostics via an MCP server published on the official MCP Registry as io.github.JDoornink/k8gents. The hard problems — confidence calibration, LLM vs deterministic routing, evaluating for unanticipated failures — are openly documented in the README.
↗OmniSight-Core
A production-grade video search engine capable of understanding semantic queries (e.g., "Find a red truck at night"). Demonstrates self-healing infrastructure that automatically detects model performance decay and triggers retraining.
agent-lint-cli
ESLint for agents. A published Python CLI tool that validates MCP servers and scans AI agent implementations for security vulnerabilities. Supports configurable security levels, CI/CD integration with threshold-based failure conditions, and multiple output formats including SARIF.
↗Agentic SRE Pipeline & Portfolio
The source code driving this exact platform. A Next.js (React) infrastructure executing a Python/RAG Agent pipeline that strictly parses unstructured Job Descriptions and outputs statically generated, targeted frontend bundles dynamically.
Certifications & Courses
Skills
Professional Experience
REASON BENEFIT AI CORPORATION
🚀 Startup- Architect and maintain large-scale Azure Kubernetes Service (AKS) production environment for ML model training and serving, supporting distributed model inference at scale.
- Integrate with Azure offerings for resource utilization across distributed training systems.
- Collaborate with research teams to translate desired microservice architectures into cloud-based systems with focus on reliability and scalability.
- Drive distributed training pipeline creation by introducing automated pipeline scripts and validations to reduce training cycle time.
Trimble/Viewpoint
- Built and maintained Human Resources Information management system, responsible for over $8.3M+ in ARR and 43% YoY growth rate.
- Architected AKS production environments handling 14K+ requests/day across 30+ microservices at 99.9% uptime SLA.
- Built automation tooling in Python and Go eliminating 80+ hours/month of toil and accelerating deployment velocity 3x.
- Developed YAML-based orchestration pipelines, reducing manual overhead by 70%.
- Reduced P99 latency 45% and improved throughput 60% through systematic profiling of distributed systems.
- Developed Go CLI tooling (Cobra) adopted by 50+ engineers for streamlined infrastructure workflows in the organization.
- Implemented New Relic observability stack with distributed tracing, cutting MTTR by 50%.
- Led Kubernetes capacity planning and auto-scaling strategies supporting 200% traffic growth.
- Built CI/CD pipelines (GitHub Actions, Azure DevOps) with automated testing and rollback mechanisms.
- Managed 100+ cloud resources via Terraform IaC; implemented CKS security controls for SOC2 compliance.
- Integrated services with event-driven architecture using Kafka and Redis, improving system decoupling and scalability.
- Mentored junior engineers and led knowledge-sharing sessions on Kubernetes best practices and SRE principles.
- Maintained pipelines across multiple teams and Cloud platforms (Azure, AWS) for consistency across products in the organization.
Viewpoint
- Developed cloud-based SaaS applications using .NET and Angular, migrating on-premise software solutions to Azure cloud platform.
- Built RESTful APIs for multi-tenant applications serving thousands of users with focus on performance and scalability.
Onfulfillment
- Engineered multi-tenant e-commerce platform using Microsoft Stack (.NET, C#, SQL Server) integrated with third-party SaaS APIs.
- Led 'uplift' initiative migrating legacy codebase to modern greenfield platform, improving response times by 40% measured through New Relic APM.
Legacy Biomechanics Research Lab
- Lead Test and Development Engineer for NIH-funded multimillion-dollar research project focused on bone fixation solutions.
- Managed successful implant creation, delivery, and test methodology producing multiple US FDA-approved implants.
Publications
M Bottlang, J Doornink, DC Fitzpatrick, SM Madey
M Bottlang, J Doornink, GD Byrd, DC Fitzpatrick, SM Madey
DC Fitzpatrick, J Doornink, SM Madey, M Bottlang
M Bottlang, M Lesser, J Koerber, J Doornink, B von Rechenberg, P Augat, DC Fitzpatrick, SM Madey, JL Marsh
M Bottlang, J Doornink, TJ Lujan, DC Fitzpatrick, JL Marsh, P Augat, B von Rechenberg, M Lesser, SM Madey
J Doornink, DC Fitzpatrick, S Boldhaus, SM Madey, M Bottlang
J Doornink, DC Fitzpatrick, SM Madey, M Bottlang
PJ Denard, J Doornink, D Phelan, SM Madey, DC Fitzpatrick, M Bottlang
PA Wackym, JA Ratigan, JD Birck, SH Johnson, J Doornink, M Bottlang, SK Gardiner, FO Black
M Bottlang, DC Fitzpatrick, D Sheerin, E Kubiak, R Gellman, C Vande Zandschulp, J Doornink, K Earley, SM Madey