01 / The beginning
High School · A curious mind
Every story starts somewhere.
A kid who asked too many questions discovered that ideas could become things—and that learning could be its own kind of adventure.
Bosit AnvarovHigh School · 01 / 06
Software engineer · Building toward AI/ML
Every system
has a story.
Scroll through the moments that shaped the person behind the code—from a curious kid to a software engineer building reliable systems and working toward the next generation of AI.
35M+Daily rail sensor readings supported
1M+Cloud records queried through AWS Athena
1,000+Services considered in scalable alert architecture
100+Applications supported during observability migration
02 / Experience
Production work, measured in systems and outcomes.
Experience across cloud platforms, enterprise applications, and observability tooling—with an emphasis on making operational complexity easier to reason about.
01
May 2025 – Present
BNSF Railway
Software Engineer I · Fort Worth, Texas · Remote/Hybrid as applicable
Production systems that make high-volume operational data useful and actionable.
Focus · Cloud systems, IoT data, backend services, observability
- Integrated Spring Boot services with Kafka-based workflows supporting more than 35 million daily rail sensor readings.
- Built a backend microservice using REST APIs, AWS Athena, S3, and Glue to query more than 1 million operational records.
- Developed Python-based Observability-as-Code tooling to provision JSON-defined alerts into Grafana and vmalert.
- Designed a scalable alert architecture intended to support more than 1,000 services.
- Reduced repeat on-call pages by approximately 40% by developing Java guardrails that improved alert actionability.
- Supported observability migration work across more than 100 applications.
JavaSpring BootKafkaAWS AthenaS3AWS GlueOIDCPythonGrafanaOpenTelemetryvmalert
02
June 2024 – March 2025
Cencora
Software Developer Intern · United States
Automation and secure delivery work across enterprise application teams.
Focus · Enterprise applications, automation, EDI systems
- Automated database transfer workflows, improving team productivity by approximately 30%.
- Contributed to four enterprise applications built with Spring Boot, Angular, and Oracle.
- Supported CI/CD workflows with Jenkins.
- Addressed static-analysis findings and maintained secure delivery standards through Checkmarx.
JavaSpring BootAngularOracleJenkinsCheckmarx
03
January 2024 – June 2024
Sensoria Health
Software Engineer Intern · Redmond, Washington
Accessible healthcare workflows grounded in accurate patient-facing data.
Focus · Healthcare software, accessibility, backend services
- Collaborated across more than 50 requirements and design discussions for healthcare software and .NET microservices.
- Identified and resolved more than 15 metric inaccuracies in patient-facing dashboards.
- Developed a JavaScript language-switching feature supporting English, Italian, and Japanese.
- Improved accessibility and usability for multilingual users monitoring patient progress.
.NETC#JavaScriptAzure FunctionsMicroservices
03 / Selected projects
From reliable systems to intelligent products.
Selected work across cloud infrastructure, distributed computing, machine learning, computer vision, and full-stack product delivery.
OBS / 01
Cloud & Infrastructure
Observability-as-Code Platform
A configuration-driven alert provisioning system for creating and managing monitoring rules at scale.
ATHENA
Cloud & Infrastructure
Cloud Operational Data Query Service
A Spring Boot backend service that securely queries cloud-hosted operational data through AWS Athena.
WEATHER
Distributed Systems
Distributed Weather Alert System
A distributed weather notification system comparing Java RMI callbacks with gRPC streaming.
ROP
Machine Learning
Retinopathy of Prematurity Classification
An explainable, patient-aware retinal-image classification workflow designed to prevent patient-level data leakage.
WAVE
Distributed Systems
Parallel Wave Simulation
A C++ parallel-computing project focused on accelerating numerical wave simulation workloads.
MOBILE-M
Full Stack
Mobile Application MVP
A mobile product MVP built with React Native and a Spring Boot backend deployed on AWS.
04 / Education
Systems thinking, expanded through AI/ML research.
University of Washington Bothell · a foundation spanning distributed systems, parallel computing, machine learning, computer vision, and software engineering.
Master's degree
Master of Science in Computer Science or Computer Science and Software Engineering
Distributed SystemsParallel ProgrammingMachine LearningSoftware Research MethodsComputer VisionAdvanced software and systems topics
Bachelor's degree
Bachelor of Science in Computer Science and Software Engineering
Data StructuresAlgorithmsComputer ArchitectureOperating SystemsDatabase SystemsDistributed SystemsParallel Programming
Academic highlights
Curiosity across systems and intelligence.
- CS Peer Facilitator / Grader
- iBioML research experience
- Distributed weather-alert research project
- Parallel and distributed-computing coursework
- Retinopathy of Prematurity machine-learning research
Awards, scholarships, publications, Dean’s List terms, conference presentations, and research links: [Add if applicable]
05 / Capabilities
The engineering foundation behind intelligent products.
Backend, cloud, distributed systems, observability, and applied machine learning—the layers I’m bringing together to build dependable, production-ready AI.
01
Backend & APIs
JavaSpring BootC#.NETREST APIsMicroservicesJUnit
02
Cloud & Infrastructure
AWSAthenaS3GlueEC2RDSCloudFrontAzure FunctionsOIDCDockerJenkins
03
Distributed Systems & Messaging
KafkaJava RMIgRPCOpenTelemetryParallel programmingDistributed-system architecture
04
Observability & Reliability
GrafanavmalertObservability-as-CodeAlert designMonitoring architectureProduction support
05
Frontend & Mobile
JavaScriptTypeScriptReactReact NativeAngularTailwind CSS
06
AI, Machine Learning & Data
Pythonpandasscikit-learnComputer VisionModel EvaluationExplainable AILIMESQL
06 / Contact
Let’s build the next generation of intelligent systems.
I’m interested in software and AI/ML engineering opportunities where machine learning meets backend platforms, cloud infrastructure, distributed systems, and observability—turning intelligent ideas into dependable products.