Josef Doornink
Site Reliability Engineer | AI Infrastructure & MLOps
Site Reliability Engineer with 12+ years specializing in distributed systems, cloud infrastructure, and large-scale Kubernetes environments (CKS/CKA certified). Focused on building platform tooling that drives engineering productivity and eliminates toil. Currently bridging SRE and AI by scaling MLOps pipelines and model serving infrastructure. Deep expertise in observability, performance tuning, and infrastructure automation.
Certifications
Featured Architecture & Tooling
K8gentS
An autonomous Root Cause Analysis (RCA) agent designed specifically for Kubernetes clusters. Leverages LLM logic and system telemetry to automatically diagnose pod failures, resource exhaustion, and network bottlenecks, drastically reducing operational MTTR.
OmniSight-Core
A centralized observability and anomaly detection platform for distributed microservices. Engineered to aggregate telemetry, system metrics, and distributed traces into actionable infrastructure insights.
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.
Aggregated Skills
Professional Experience - Startup
REASON BENEFIT AI CORPORATION
- Architect and maintain large-scale Azure Kubernetes Service (AKS) production environment for ML model training and serving, supporting distributed model inference at scale.
- Build Python-based automation tools for ML pipeline orchestration, reducing manual overhead by 70% and accelerating model deployment velocity.
- Integrate with observability frameworks for model performance tracking, latency monitoring, and resource utilization across distributed training systems.
- Optimize model serving infrastructure through performance profiling and system-level optimizations, improving inference throughput by 40%.
- Collaborate with research teams to translate experimental model architectures into production-ready systems with focus on reliability and scalability.
- Implement automated testing frameworks for ML pipelines to quickly detect regressions and ensure model quality in production.
Professional Experience
Trimble/Viewpoint
- Architected and maintained large-scale Azure Kubernetes Service (AKS) production environments handling 10M+ requests/day across 30+ microservices with 99.9% uptime SLA.
- Developed high-performance automation tools using Python and Go that eliminated 80+ hours/month of operational toil, accelerating deployment velocity by 3x across engineering teams.
- Led performance optimization initiatives through systematic profiling and instrumentation, reducing P99 latency by 45% and improving throughput by 60% for distributed systems.
- Built custom CLI tooling in Go (Cobra framework) to streamline workflows for 50+ engineers, dramatically improving team productivity through better developer experience.
- Designed and implemented comprehensive observability stack (Prometheus, Grafana, Azure Monitor) with distributed tracing for debugging performance bottlenecks in distributed microservices.
- Led capacity planning and performance optimization for Kubernetes clusters and backend databases, implementing auto-scaling strategies supporting 200% traffic growth.
- Created sophisticated CI/CD pipelines using GitHub Actions and Azure DevOps with automated testing, sophisticated deployment templates, and rollback mechanisms.
- Implemented Infrastructure as Code using Terraform managing 500+ cloud resources, enabling consistent and repeatable infrastructure provisioning.
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 (Subset of 11)
Far cortical locking can reduce stiffness of locked plating constructs while retaining construct strength
M Bottlang, J Doornink, DC Fitzpatrick, SM Madey
Far cortical locking can improve healing of fractures stabilized with locking plates
M Bottlang, M Lesser, J Koerber, J Doornink, S Mueller, DC Fitzpatrick...
Effects of construct stiffness on healing of fractures stabilized with locking plates
M Bottlang, J Doornink, TJ Lujan, DC Fitzpatrick, PV Marsh...
Far cortical locking enables flexible fixation with periarticular locking plates
J Doornink, DC Fitzpatrick, SM Madey, M Bottlang
Effects of hybrid plating with locked and nonlocked screws on the strength of locked plating constructs in the osteoporotic diaphysis
J Doornink, DC Fitzpatrick, S Boldhaus, SM Madey, M Bottlang