# Jason Huling - Software Engineer - Infra, Platforms, Data & ML Systems

Last updated: 2026-06-09
Canonical URL: https://jason.huln.dev/
Structured JSON: https://jason.huln.dev/portfolio.json
LLM summary: https://jason.huln.dev/llms.txt

## Summary

Engineer and architect with 11 years building cloud infrastructure, platform tooling, data systems, and backend services, including pipelines that stream 35M+ events/hour.

- Now: Director of Technical Operations, Blooma
- Focus: Infrastructure, platform engineering, backend, and data/ML systems
- Primary stack: Python, Go, AWS, Kubernetes, Terraform, Postgres, MongoDB, React
- Based: California, America/Los_Angeles

## Metrics

- 35M+ events/hour through data pipelines
- $180K+ annual infra/tooling savings
- 100+ technical users enabled on ML platforms
- SOC 2 technical controls owned
- 11 yrs ops → data/ML → platforms → software

## Capabilities

### Platform & Infrastructure

Designing cloud foundations, deployment workflows, and internal platforms that help product teams move safely.

Evidence: 30K+ Terraform-managed resources across cloud environments.

Tools and systems: AWS, Terraform, Kubernetes, GitOps, CI/CD

### Backend & Systems Software

Building services, libraries, APIs, and integration layers for product and platform systems.

Evidence: Python library ecosystem for secure clients, resource management, and workflow automation.

Tools and systems: Python, Go, REST APIs, CloudEvents, Postgres

### Data & ML Systems

Connecting data pipelines, ML workflows, and model-serving infrastructure to practical product outcomes.

Evidence: 100+ technical users enabled on ML platforms and 20+ ML models deployed.

Tools and systems: MLOps, Spark, PySpark, Kubeflow, Data Pipelines

### Reliability, Security & Operations

Owning the operational systems that keep production software observable, recoverable, and audit-ready.

Evidence: 35M+ events/hour through telemetry pipelines across accounts, regions, and clusters.

Tools and systems: Observability, SOC 2, AWS Lambda, Kinesis Firehose, BC/DR

### Technical Leadership

Translating business goals into technical direction, mentoring engineers, and aligning stakeholders around durable systems.

Evidence: Led architecture across startup infrastructure and global Cisco data-science teams.

Tools and systems: Architecture, Strategy, Mentoring, Stakeholder Alignment

## Selected Work

### Distributed AI/ML Messaging System
Role: Designed & Built
Date: 2024-25
Technologies: Python, AWS, CloudEvents, Lambda, Vercel
Designed and built a CloudEvents-based messaging system on AWS to connect AI/ML inference services, backend workflows, and product-facing applications. Built Python libraries and middleware to standardize message construction, routing, and service integration across a rapidly evolving system.
### Centralized Observability Pipelines
Role: Designed & Built
Date: 2022-24
Impact: 35M/hr events streamed
Technologies: AWS, Kinesis Firehose, Lambda, Python
Built centralized observability pipelines across AWS accounts, regions, and Kubernetes clusters to stream security, infrastructure, and application telemetry into a unified platform. Designed the system for high-volume ingestion, resiliency, operational visibility, and real-time alerting, supporting 35M+ events/hour.
### Enterprise Python Library Ecosystem
Role: Designed & Built
Date: 2022-24
Technologies: Python, Kubernetes
Built a Python library ecosystem to deliver and support mission-critical products, including frameworks for secure HTTP/REST API clients, data masking and troubleshooting utilities, declarative resource management, API integrations, data exports, flexible configuration, credential management, and Kubernetes CRD-based workflow automation.
### AWS Terraform Landing Zone
Role: Designed & Built
Date: 2022-24
Impact: 30K+ resources managed
Technologies: Terraform, AWS, Python
Designed and developed Terraform GitOps workflows and an AWS landing zone with account vending, security baselines, and standardized infrastructure patterns. Scaled the platform to manage 30,000+ resources across cloud environments.
### Terraform GitOps Platform Migration
Role: Migrated & Owned
Date: 2024-24
Impact: $120K/yr annual savings
Technologies: Terraform, GitOps, AWS
Migrated 270+ Terraform workspaces between IaC GitOps platforms, reducing platform spend by a projected $120K annually while preserving deployment continuity across production infrastructure.
### SOC 2 Technical Controls
Role: Technical Owner
Date: 2022-now
Impact: SOC 2 controls owned
Technologies: AWS, Terraform, Kubernetes, Python
Owned technical security and compliance controls for SOC 2, including infrastructure hardening, access controls, observability, backup and recovery processes, and operational evidence collection.
### GCP ML Development Platform
Role: Designed & Built
Date: 2019-20
Impact: 100+ technical users enabled
Technologies: GCP, Terraform, Kubernetes, Kubeflow, Python
Architected a GCP-based ML development platform and MLOps workflow for global data science teams deploying production services and pipelines.
### Elasticsearch GKE Migration
Role: Migrated & Owned
Date: 2018-19
Impact: $60K/yr annual savings
Technologies: Elasticsearch, GKE, Kubernetes, Docker
Migrated Elasticsearch from a managed internal service to GKE, preserving critical search and analytics workflows while reducing cost.
### On-Prem Jupyter & Spark Platform
Role: Designed & Built
Date: 2018-19
Impact: 20+ ML models deployed
Technologies: Jupyter, PySpark, Hadoop, Python
Built an on-prem Jupyter and PySpark development platform on Hadoop, adopted by data scientists and engineers for production ML workflows.
### Hadoop Job Management CLI
Role: Designed & Built
Date: 2018-19
Impact: 100+ jobs scheduled
Technologies: Python, Hadoop, Spark, Bash
Built a Hadoop job management CLI that improved developer workflows and scheduling reliability across data science, engineering, and analytics teams.
## Independent Work

### terraform-provider-label
Role: Solo · OSS
Date: 2026-now
Status: Published · OSS
Link: https://github.com/jhulndev/terraform-provider-label
Technologies: Go, Terraform, OpenTofu
A Terraform/OpenTofu provider for consistent, convention-driven resource labeling — published to both the Terraform and OpenTofu registries. Go, provider-framework internals, and release automation.
### Audit Event Platform
Role: Solo · full-stack
Date: 2026-now
Status: In progress · not yet deployed
Technologies: React, Python, Postgres, Tailwind, Cloudflare, AWS
Building a full-stack audit event platform for capturing, querying, and replaying compliance-grade product events. Focused on API design, data modeling, immutable storage, event mutation workflows, and developer-facing product ergonomics.
## Experience

### Director of Technical Operations - Blooma

Date: Mar 2022 - now
Type: full-time, remote
Context: Seed → Series A FinTech
Technologies: Python, Terraform, Kubernetes, AWS, MongoDB, Dagster, dbt, Snowflake, Java

- Own Blooma's production infrastructure, platform tooling, data operations, and service delivery patterns - covering Kubernetes, observability, SOC 2 controls, BC/DR, data analytics, GitOps, and operations software
- Designed Terraform GitOps workflows and a Landing Zone with account vending and security baselines - currently managing 30,000+ resources
- Led infrastructure and tooling consolidation across Terraform GitOps platforms - saving a projected $120,000 annually
- Set the operating model for centralized telemetry across cloud accounts, regions, and clusters - streaming telemetry from 17 accounts, 16 regions, and 4 clusters at 35M+ events per hour
- Built and guided Python platform libraries that reduced repeated product and operations work - secure REST clients, a declarative resource manager, CRD operators, data-masking and credential utilities

### Senior DevOps Engineer - Blooma

Date: Mar 2020 - Mar 2022
Type: full-time, remote
Context: Seed → Series A FinTech
Technologies: Python, Terraform, Kubernetes, AWS, MongoDB

- Joined during the early startup stage to build the cloud, IaC, and Kubernetes foundation - patterns later scaled across infrastructure, CI/CD, and platform operations
- Established deployment and operational workflows for a growing product engineering team - making production infrastructure more repeatable as the company moved toward Series A scale

### Data Architect - Independent

Date: Aug 2024 - Dec 2025
Type: consulting, remote
Context: Consulting · Early-stage tech startup
Technologies: Python, Terraform, AWS, MongoDB, Vercel, CloudEvents

- Owned architecture for an early-stage AI/ML product system as an independent consultant - translating product needs into service boundaries, messaging patterns, and deployment choices
- Built CloudEvents-based messaging libraries and middleware across AWS and product-facing services - standardizing how inference services, backend workflows, and applications communicate
- Developed ML-facing services, Lambda functions, data pipelines, and observability hooks - integrating ML inference with Vercel apps, plus ML observability — logging, tracing, shadow testing

### Technical Lead — ML Engineering - Cisco

Date: Oct 2019 - Mar 2020
Type: full-time, remote
Context: CX / Digital Lifecycle Journeys
Technologies: Spark, PySpark, Python, Terraform, GCP, Kubernetes, Kubeflow, Dataproc

- Led architecture for DLJ's MLOps and data-science development platform - enabling data scientists to deploy scalable, production-quality ML services and pipelines
- Translated global data-science needs into shared infrastructure and platform direction - supporting 60+ technical users across six global and three regional teams; consulted across Cisco toward 100+ users
- Drove technical deep-dive sessions with SVP and Directors - translating engineering work into strategic goals — increasing executive trust and buy-in
- Led Terraform/IaC adoption across global Cisco data-science teams - standard modules for consistent, secure provisioning; reduced onboarding time

### Machine Learning Systems Developer - Cisco

Date: Aug 2017 - Oct 2019
Type: full-time
Context: CX / Digital Lifecycle Journeys
Technologies: Spark, PySpark, Python, Jupyter, Hadoop, Kubernetes, GKE, Elasticsearch, GCP, TensorFlow

- Received Technical Excellence — “The Award of All Awards” from Director and peers - for transformative innovation and technical achievement
- Turned data-science workflow friction into shared development platforms and automation - adopted by 30+ data scientists with 20+ ML models deployed; presented at 2018 Data Symposium
- Built tooling that made production data jobs easier to schedule, inspect, and maintain - 100+ jobs and 300+ source files scheduled across data science, engineering, and analytics
- Migrated an Elasticsearch cluster to GKE from a Cisco-managed instance - saving over $60K a year
- Mentored a team of 5 data scientists - code reviews, optimizations, and production-quality PySpark on large datasets

### Custom Application Engineer - Cisco

Date: Feb 2016 - Aug 2017
Type: full-time
Context: CX / Digital Lifecycle Journeys
Technologies: Spark, Scala, R, Tableau, Databricks, AWS, Docker, RabbitMQ

- Received the Connect Everything award from VP and peers - for leadership in data-lake implementation, mentorship, and advancing team technology
- Technical and project lead for exposing ML models through service-oriented interfaces - horizontally scalable, message- and container-based microservice architecture
- Developed Scala interfaces for Spark JDBC and MongoSpark, plus parquet optimizations - used by Data Engineering and DQA teams to speed up pipelines
- Applied data analytics and ML to optimize monthly renewal-campaign workflows - including an NLP de-duplication solution in R

### Software Engineer - MaintenanceNet

Date: Jul 2014 - Feb 2016
Type: full-time
Context: Acquired by Cisco · 2015
Technologies: SQL, SQL Server, XPath, XSLT, HTML

- Designed annuity and inventory data structures for Cisco Impact after the acquisition - and translated import business rules from legacy SQL to XPath
- Technical lead for the reporting team - designed and implemented core reports and a report-building interface across sites
- Led and trained new developers - establishing patterns as the team grew through the acquisition

### Business Analyst - MaintenanceNet

Date: Jan 2014 - Jul 2014
Type: full-time
Context: Acquired by Cisco · 2015
Technologies: VB.NET, SQL, SQL Server, XPath, VBA, Excel

- Bridged business operations and engineering during the move into software - translating campaign requirements into the data and tooling that delivered them

### Business Operations Associate - MaintenanceNet

Date: Jun 2013 - Jan 2014
Type: full-time
Context: Acquired by Cisco · 2015
Technologies: VB.NET, SQL, SQL Server, VBA, Excel

- Owned AutoQuote campaign delivery and quality - while automating manual processes with VBA to cut errors and lift team efficiency — where the engineering started
- Built .NET applications to retrieve and parse XML requests and report on campaign metrics - the first systems that turned an ops problem into a software one

## How I Work

My instinct is to find where my capabilities and experience can have the biggest impact.

I started in business operations, automating spreadsheet-heavy workflows because manual processes were slow and holding the entire team back. I picked up data science and machine learning through coursework in 2014, then spent the next decade filling the infrastructure and platform gaps for technical teams: ML platforms, cloud infrastructure, data systems, and tooling that made other engineers faster.

Most of what I know is self-taught and proven in production. The titles changed — engineer, lead, director — but the purpose stayed the same: find the constraint, build the system, and make the work more valuable. Starting on the business side means I tend to ask what a system is for before diving into how I'll build it.

## Working With AI

Every project carries its own risk tolerance and appetite for using AI. While AI has changed how fast I can work, it has not changed what I'm responsible for. I use it for leverage on the parts I already understand, and I don't ship anything I can't read, reason about, and defend.

## Contact

- Email: contact@sl.huln.dev
- GitHub: https://github.com/jhulndev
- LinkedIn: https://www.linkedin.com/in/jasonhuling