TYLER REAGAN
PersonalResume

About Me

Full-stack and platform engineer with 6+ years of experience building at high-velocity startups. Proven track record of end-to-end technical ownership. I excel in ambiguous environments requiring fast ramp-up and attention to detail.

Skills

Full-Stack Development

End-to-end product delivery of both web and desktop applications

TypeScript
React
Next.js
Node.js
Electron
Backend & Distributed Systems

Service design, API contracts, and durable workflow orchestration

gRPC
REST
Go
Temporal
MongoDB
AI & Agent Systems

Agent orchestration, tool-calling protocols, and platform design

MCP
Strands SDK
AWS Bedrock
Firecracker
Skills
Cloud & Infrastructure

AWS, containerization, IaC, observability, auth, and CI/CD

AWS
Docker
GitLab CI/CD
Kubernetes
k9s
Terraform
Datadog
Auth0
Data Engineering

Pipeline orchestration, warehousing, and in-process analytics

Apache Airflow
DuckDB
Apache Parquet
Python
SQL

Experience

▸Design and maintain data models and API contracts across a distributed Go/gRPC microservice fleet powering a multi-tenant platform.

–Architected a Temporal workflow and its concurrency patterns to enable self-service restoration of S3 Glacier data.

–Implemented an internal Kubernetes helper library as part of hardening job runner design and workload handling.

–Monitor service health and error traces across distributed services using Datadog.

▸Productionalized CytoCanvas™, a multi-platform, cloud-enabled cell visualization product for life science research.

–Consistently design and implement data format and processing pipelines to optimize performance with respect to reducing latency.

–Architected a shared core framework for standardization across platforms, significantly reducing maintained surface area and accelerating feature development.

–Refactored frontend state management and component architecture using Zustand and Material UI to stabilize UI performance and enhance UX.

–Hardened Electron desktop infrastructure by building a type-safe IPC bridge, secure code-signing pipeline, and version-gated auto-updater.

▸Core IC of an AI chat product — built streaming transport layers across React, Go, and AWS Bedrock/Gateway using a gRPC BFF architecture.

–Designed resilient session-oriented connection handling to maintain execution state during intermittent network drops and long-running agent workflows.

–Evaluated and integrated emerging agent tool-calling frameworks and protocols (MCP, Plugins, Strands SDK).

▸Core IC of an AI compute platform — engineered interactive execution and observation capabilities via MCP to expose stateful Python runtimes to LLM agents.

–Implemented detached process execution, over-the-wire cancellation, and durable output persistence (mount/fsync) for session-oriented, long-running agent tasks.

–Partnered directly with life-science domain experts to translate complex research workflows into production-grade, highly reliable execution environments.

–Architected session lifecycle workflows (create, hibernate, resume, resize) and control plane IPC primitives for Firecracker microVMs.

TypeScript
React
Next.js
Electron
Go
gRPC
MCP
Firecracker
AI
AWS
Terraform
Temporal
Kubernetes
Datadog
MongoDB
Auth0
DuckDB
Docker

▸Owned and modernised core clinical research data infrastructure, scaling throughput for cross-functional research teams.

–Engineered Go-based ETL pipelines to deliver deterministic, versioned datasets for high-compliance clinical workflows.

–Introduced Apache Airflow (AWS MWAA), evolving it into the platform’s primary orchestration backbone for complex data DAGs.

▸Architected a comprehensive infrastructure overhaul, modernizing build systems, deployment pipelines, and cloud resources.

–Reduced Terraform file overhead by 94% (520 files down to 29) by consolidating around Go binaries (Bazel) and EKS Kubernetes pod operators.

–Standardized production workflow orchestration using Python-based Airflow DAGs targeting containerized cluster runtimes.

▸Optimized EKS cluster resource utilization and cloud spend across production compute workloads.

–Reduced Kubernetes pod memory consumption by up to 30% by offloading heavy in-memory operations to managed AWS data services.

Go
Apache Airflow
Terraform
AWS
Kubernetes
Bazel
Python
Docker
GitLab CI

▸Engineered high-throughput Go ETL pipelines processing real-time revenue and engagement metrics across thousands of publisher sites.

–Designed concurrent data transformation services in Go to handle high-volume, low-latency ad metrics ingestion.

–Ensured data accuracy and auditability for financial revenue processing across large-scale publisher networks.

▸Managed ad-tech scale streaming and data warehouse infrastructure leveraging core AWS distributed services.

–Architected event-driven streaming pipelines using AWS Kinesis, SNS, S3, and Redshift to process billions of daily events.

–Optimized Redshift schema design and query execution to accelerate analytics reporting for downstream ad-tech workloads.

Go
AWS
Apache Airflow
Python

Get In Touch

I'm currently open to new opportunities. Whether you have a question, a role in mind, or just want to say hi, my inbox is always open.

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Designed & built by Tyler Reagan