{"schemaVersion":"1.0","lastUpdated":"2026-06-09","canonicalUrl":"https://jason.huln.dev","sources":{"website":"https://jason.huln.dev","llms":"https://jason.huln.dev/llms.txt","markdown":"https://jason.huln.dev/portfolio.md","json":"https://jason.huln.dev/portfolio.json"},"profile":{"name":"Jason Huling","email":"contact@sl.huln.dev","location":{"timezone":"America/Los_Angeles"},"social":{"github":"https://github.com/jhulndev","linkedin":"https://www.linkedin.com/in/jasonhuling"},"now":"Director of Technical Operations","focus":"Infrastructure, platform engineering, backend, and data/ML systems","stack":["Python","Go","AWS","Kubernetes","Terraform","Postgres","MongoDB","React"],"availability":{"label":"Building useful systems with thoughtful teams","blurb":"Always glad to connect with teams solving meaningful problems across product, infrastructure, data, and AI/ML systems."}},"summary":{"headline":"Software Engineer - Infra, Platforms, Data & ML Systems","framing":"Engineer and architect building infrastructure, platform tooling, data systems, backend services, and ML systems that turn business problems into working software.","about":["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."],"workingWithAi":"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."},"metrics":[{"value":"35M+","label":"events/hour through data pipelines"},{"value":"$180K+","label":"annual infra/tooling savings","positive":true},{"value":"100+","label":"technical users enabled on ML platforms"},{"value":"SOC 2","label":"technical controls owned"},{"value":"11 yrs","label":"ops → data/ML → platforms → software"}],"capabilities":[{"id":"cap-platform-infrastructure","title":"Platform & Infrastructure","description":"Designing cloud foundations, deployment workflows, and internal platforms that help product teams move safely.","technologies":["AWS","Terraform","Kubernetes","GitOps","CI/CD"],"evidence":"30K+ Terraform-managed resources across cloud environments."},{"id":"cap-backend-systems","title":"Backend & Systems Software","description":"Building services, libraries, APIs, and integration layers for product and platform systems.","technologies":["Python","Go","REST APIs","CloudEvents","Postgres"],"evidence":"Python library ecosystem for secure clients, resource management, and workflow automation."},{"id":"cap-data-ml-systems","title":"Data & ML Systems","description":"Connecting data pipelines, ML workflows, and model-serving infrastructure to practical product outcomes.","technologies":["MLOps","Spark","PySpark","Kubeflow","Data Pipelines"],"evidence":"100+ technical users enabled on ML platforms and 20+ ML models deployed."},{"id":"cap-reliability-security","title":"Reliability, Security & Operations","description":"Owning the operational systems that keep production software observable, recoverable, and audit-ready.","technologies":["Observability","SOC 2","AWS Lambda","Kinesis Firehose","BC/DR"],"evidence":"35M+ events/hour through telemetry pipelines across accounts, regions, and clusters."},{"id":"cap-technical-leadership","title":"Technical Leadership","description":"Translating business goals into technical direction, mentoring engineers, and aligning stakeholders around durable systems.","technologies":["Architecture","Strategy","Mentoring","Stakeholder Alignment"],"evidence":"Led architecture across startup infrastructure and global Cisco data-science teams."}],"projects":[{"id":"proj-distributed-messaging","name":"Distributed AI/ML Messaging System","description":"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.","role":"Designed & Built","experienceId":"exp-data-architect-2024","startDate":"2024-08-01","endDate":"2025-12-30","technologies":["Python","AWS","CloudEvents","Lambda","Vercel"],"featured":true,"tags":["aws","python","ml"],"kind":"selected","displayDate":"2024-25","context":{"experienceId":"exp-data-architect-2024","role":"Data Architect","company":"Independent"}},{"id":"proj-observability-pipelines","name":"Centralized Observability Pipelines","description":"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.","role":"Designed & Built","experienceId":"exp-director-ops-2022","startDate":"2022-09-01","endDate":"2024-06-01","technologies":["AWS","Kinesis Firehose","Lambda","Python"],"impact":{"metric":"events streamed","value":"35M/hr"},"featured":true,"tags":["aws","python","kubernetes","observability"],"kind":"selected","displayDate":"2022-24","context":{"experienceId":"exp-director-ops-2022","role":"Director of Technical Operations","company":"Blooma"}},{"id":"proj-python-library-ecosystem","name":"Enterprise Python Library Ecosystem","description":"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.","role":"Designed & Built","experienceId":"exp-director-ops-2022","startDate":"2022-06-01","endDate":"2024-06-01","technologies":["Python","Kubernetes"],"tags":["python","kubernetes"],"kind":"selected","displayDate":"2022-24","context":{"experienceId":"exp-director-ops-2022","role":"Director of Technical Operations","company":"Blooma"}},{"id":"proj-terraform-landing-zone","name":"AWS Terraform Landing Zone","description":"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.","role":"Designed & Built","experienceId":"exp-director-ops-2022","startDate":"2022-06-01","endDate":"2024-06-01","technologies":["Terraform","AWS","Python"],"impact":{"metric":"resources managed","value":"30K+"},"tags":["aws","terraform","python"],"kind":"selected","displayDate":"2022-24","context":{"experienceId":"exp-director-ops-2022","role":"Director of Technical Operations","company":"Blooma"}},{"id":"proj-terraform-gitops-migration","name":"Terraform GitOps Platform Migration","description":"Migrated 270+ Terraform workspaces between IaC GitOps platforms, reducing platform spend by a projected $120K annually while preserving deployment continuity across production infrastructure.","role":"Migrated & Owned","experienceId":"exp-director-ops-2022","startDate":"2024-01-01","endDate":"2024-06-01","technologies":["Terraform","GitOps","AWS"],"impact":{"metric":"annual savings","value":"$120K/yr"},"tags":["terraform","gitops","aws","cost-optimization"],"kind":"selected","displayDate":"2024-24","context":{"experienceId":"exp-director-ops-2022","role":"Director of Technical Operations","company":"Blooma"}},{"id":"proj-soc2-controls","name":"SOC 2 Technical Controls","description":"Owned technical security and compliance controls for SOC 2, including infrastructure hardening, access controls, observability, backup and recovery processes, and operational evidence collection.","role":"Technical Owner","experienceId":"exp-director-ops-2022","startDate":"2022-03-01","technologies":["AWS","Terraform","Kubernetes","Python"],"impact":{"metric":"controls owned","value":"SOC 2"},"tags":["aws","security","terraform","kubernetes"],"kind":"selected","displayDate":"2022-now","context":{"experienceId":"exp-director-ops-2022","role":"Director of Technical Operations","company":"Blooma"}},{"id":"proj-ml-platform-gcp","name":"GCP ML Development Platform","description":"Architected a GCP-based ML development platform and MLOps workflow for global data science teams deploying production services and pipelines.","role":"Designed & Built","experienceId":"exp-tech-lead-ml-2019","startDate":"2019-10-01","endDate":"2020-03-01","technologies":["GCP","Terraform","Kubernetes","Kubeflow","Python"],"impact":{"metric":"technical users enabled","value":"100+"},"tags":["gcp","terraform","kubernetes","ml","python"],"kind":"selected","displayDate":"2019-20","context":{"experienceId":"exp-tech-lead-ml-2019","role":"Technical Lead — ML Engineering","company":"Cisco"}},{"id":"proj-elasticsearch-migration","name":"Elasticsearch GKE Migration","description":"Migrated Elasticsearch from a managed internal service to GKE, preserving critical search and analytics workflows while reducing cost.","role":"Migrated & Owned","experienceId":"exp-ml-systems-dev-2017","startDate":"2018-09-01","endDate":"2019-01-01","technologies":["Elasticsearch","GKE","Kubernetes","Docker"],"impact":{"metric":"annual savings","value":"$60K/yr"},"tags":["gcp","kubernetes","observability"],"kind":"selected","displayDate":"2018-19","context":{"experienceId":"exp-ml-systems-dev-2017","role":"Machine Learning Systems Developer","company":"Cisco"}},{"id":"proj-jupyter-spark-platform","name":"On-Prem Jupyter & Spark Platform","description":"Built an on-prem Jupyter and PySpark development platform on Hadoop, adopted by data scientists and engineers for production ML workflows.","role":"Designed & Built","experienceId":"exp-ml-systems-dev-2017","startDate":"2018-01-01","endDate":"2019-06-01","technologies":["Jupyter","PySpark","Hadoop","Python"],"impact":{"metric":"ML models deployed","value":"20+"},"tags":["data","ml","python"],"kind":"selected","displayDate":"2018-19","context":{"experienceId":"exp-ml-systems-dev-2017","role":"Machine Learning Systems Developer","company":"Cisco"}},{"id":"proj-hadoop-job-cli","name":"Hadoop Job Management CLI","description":"Built a Hadoop job management CLI that improved developer workflows and scheduling reliability across data science, engineering, and analytics teams.","role":"Designed & Built","experienceId":"exp-ml-systems-dev-2017","startDate":"2018-06-01","endDate":"2019-06-01","technologies":["Python","Hadoop","Spark","Bash"],"impact":{"metric":"jobs scheduled","value":"100+"},"tags":["data","python"],"kind":"selected","displayDate":"2018-19","context":{"experienceId":"exp-ml-systems-dev-2017","role":"Machine Learning Systems Developer","company":"Cisco"}},{"id":"proj-terraform-provider-label","name":"terraform-provider-label","description":"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.","role":"Solo · OSS","startDate":"2026-05-01","technologies":["Go","Terraform","OpenTofu"],"kind":"independent","status":"Published · OSS","link":"https://github.com/jhulndev/terraform-provider-label","linkLabel":"github.com/jhulndev/terraform-provider-label","displayDate":"2026-now"},{"id":"proj-audit-event-platform","name":"Audit Event Platform","description":"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.","role":"Solo · full-stack","startDate":"2026-01-01","technologies":["React","Python","Postgres","Tailwind","Cloudflare","AWS"],"kind":"independent","status":"In progress · not yet deployed","displayDate":"2026-now"}],"experience":[{"id":"exp-director-ops-2022","company":"Blooma","title":"Director of Technical Operations","type":"full-time","location":"Remote","remote":true,"startDate":"2022-03-01","description":"Seed → Series A FinTech","achievements":[{"id":"blooma-dir-1","description":"Own Blooma's production infrastructure, platform tooling, data operations, and service delivery patterns","impact":"covering Kubernetes, observability, SOC 2 controls, BC/DR, data analytics, GitOps, and operations software"},{"id":"blooma-dir-2","description":"Designed Terraform GitOps workflows and a Landing Zone with account vending and security baselines","impact":"currently managing 30,000+ resources"},{"id":"blooma-dir-3","description":"Led infrastructure and tooling consolidation across Terraform GitOps platforms","impact":"saving a projected $120,000 annually"},{"id":"blooma-dir-4","description":"Set the operating model for centralized telemetry across cloud accounts, regions, and clusters","impact":"streaming telemetry from 17 accounts, 16 regions, and 4 clusters at 35M+ events per hour"},{"id":"blooma-dir-5","description":"Built and guided Python platform libraries that reduced repeated product and operations work","impact":"secure REST clients, a declarative resource manager, CRD operators, data-masking and credential utilities"}],"technologies":["Python","Terraform","Kubernetes","AWS","MongoDB","Dagster","dbt","Snowflake","Java"],"displayDate":"Mar 2022 - now"},{"id":"exp-senior-devops-2020","company":"Blooma","title":"Senior DevOps Engineer","type":"full-time","location":"Remote","remote":true,"startDate":"2020-03-01","endDate":"2022-03-01","description":"Seed → Series A FinTech","achievements":[{"id":"blooma-devops-1","description":"Joined during the early startup stage to build the cloud, IaC, and Kubernetes foundation","impact":"patterns later scaled across infrastructure, CI/CD, and platform operations"},{"id":"blooma-devops-2","description":"Established deployment and operational workflows for a growing product engineering team","impact":"making production infrastructure more repeatable as the company moved toward Series A scale"}],"technologies":["Python","Terraform","Kubernetes","AWS","MongoDB"],"displayDate":"Mar 2020 - Mar 2022"},{"id":"exp-data-architect-2024","company":"Independent","title":"Data Architect","type":"consulting","location":"Remote","remote":true,"startDate":"2024-08-01","endDate":"2025-12-01","description":"Consulting · Early-stage tech startup","achievements":[{"id":"da24-1","description":"Owned architecture for an early-stage AI/ML product system as an independent consultant","impact":"translating product needs into service boundaries, messaging patterns, and deployment choices"},{"id":"da24-2","description":"Built CloudEvents-based messaging libraries and middleware across AWS and product-facing services","impact":"standardizing how inference services, backend workflows, and applications communicate"},{"id":"da24-3","description":"Developed ML-facing services, Lambda functions, data pipelines, and observability hooks","impact":"integrating ML inference with Vercel apps, plus ML observability — logging, tracing, shadow testing"}],"technologies":["Python","Terraform","AWS","MongoDB","Vercel","CloudEvents"],"displayDate":"Aug 2024 - Dec 2025"},{"id":"exp-tech-lead-ml-2019","company":"Cisco","title":"Technical Lead — ML Engineering","type":"full-time","location":"Remote","remote":true,"startDate":"2019-10-01","endDate":"2020-03-01","description":"CX / Digital Lifecycle Journeys","achievements":[{"id":"cisco-lead-1","description":"Led architecture for DLJ's MLOps and data-science development platform","impact":"enabling data scientists to deploy scalable, production-quality ML services and pipelines"},{"id":"cisco-lead-2","description":"Translated global data-science needs into shared infrastructure and platform direction","impact":"supporting 60+ technical users across six global and three regional teams; consulted across Cisco toward 100+ users"},{"id":"cisco-lead-3","description":"Drove technical deep-dive sessions with SVP and Directors","impact":"translating engineering work into strategic goals — increasing executive trust and buy-in"},{"id":"cisco-lead-4","description":"Led Terraform/IaC adoption across global Cisco data-science teams","impact":"standard modules for consistent, secure provisioning; reduced onboarding time"}],"technologies":["Spark","PySpark","Python","Terraform","GCP","Kubernetes","Kubeflow","Dataproc"],"displayDate":"Oct 2019 - Mar 2020"},{"id":"exp-ml-systems-dev-2017","company":"Cisco","title":"Machine Learning Systems Developer","type":"full-time","location":"Carlsbad, CA","remote":false,"startDate":"2017-08-01","endDate":"2019-10-01","description":"CX / Digital Lifecycle Journeys","achievements":[{"id":"cisco-ml-1","description":"Received Technical Excellence — “The Award of All Awards” from Director and peers","impact":"for transformative innovation and technical achievement","award":{"name":"Technical Excellence Award","from":"Director & peers"}},{"id":"cisco-ml-2","description":"Turned data-science workflow friction into shared development platforms and automation","impact":"adopted by 30+ data scientists with 20+ ML models deployed; presented at 2018 Data Symposium"},{"id":"cisco-ml-3","description":"Built tooling that made production data jobs easier to schedule, inspect, and maintain","impact":"100+ jobs and 300+ source files scheduled across data science, engineering, and analytics"},{"id":"cisco-ml-4","description":"Migrated an Elasticsearch cluster to GKE from a Cisco-managed instance","impact":"saving over $60K a year"},{"id":"cisco-ml-5","description":"Mentored a team of 5 data scientists","impact":"code reviews, optimizations, and production-quality PySpark on large datasets"}],"technologies":["Spark","PySpark","Python","Jupyter","Hadoop","Kubernetes","GKE","Elasticsearch","GCP","TensorFlow"],"displayDate":"Aug 2017 - Oct 2019"},{"id":"exp-custom-app-engineer-2016","company":"Cisco","title":"Custom Application Engineer","type":"full-time","location":"Carlsbad, CA","remote":false,"startDate":"2016-02-01","endDate":"2017-08-01","description":"CX / Digital Lifecycle Journeys","achievements":[{"id":"cisco-app-1","description":"Received the Connect Everything award from VP and peers","impact":"for leadership in data-lake implementation, mentorship, and advancing team technology","award":{"name":"Connect Everything Award","from":"VP & peers"}},{"id":"cisco-app-2","description":"Technical and project lead for exposing ML models through service-oriented interfaces","impact":"horizontally scalable, message- and container-based microservice architecture"},{"id":"cisco-app-3","description":"Developed Scala interfaces for Spark JDBC and MongoSpark, plus parquet optimizations","impact":"used by Data Engineering and DQA teams to speed up pipelines"},{"id":"cisco-app-4","description":"Applied data analytics and ML to optimize monthly renewal-campaign workflows","impact":"including an NLP de-duplication solution in R"}],"technologies":["Spark","Scala","R","Tableau","Databricks","AWS","Docker","RabbitMQ"],"displayDate":"Feb 2016 - Aug 2017"},{"id":"exp-software-engineer-2014","company":"MaintenanceNet","companyDetails":{"acquired":true},"title":"Software Engineer","type":"full-time","location":"Carlsbad, CA","remote":false,"startDate":"2014-07-01","endDate":"2016-02-01","description":"Acquired by Cisco · 2015","achievements":[{"id":"mnet-eng-1","description":"Designed annuity and inventory data structures for Cisco Impact after the acquisition","impact":"and translated import business rules from legacy SQL to XPath"},{"id":"mnet-eng-2","description":"Technical lead for the reporting team","impact":"designed and implemented core reports and a report-building interface across sites"},{"id":"mnet-eng-3","description":"Led and trained new developers","impact":"establishing patterns as the team grew through the acquisition"}],"technologies":["SQL","SQL Server","XPath","XSLT","HTML"],"displayDate":"Jul 2014 - Feb 2016"},{"id":"exp-business-analyst-2014","company":"MaintenanceNet","title":"Business Analyst","type":"full-time","location":"Carlsbad, CA","remote":false,"startDate":"2014-01-01","endDate":"2014-07-01","description":"Acquired by Cisco · 2015","achievements":[{"id":"mnet-ba-1","description":"Bridged business operations and engineering during the move into software","impact":"translating campaign requirements into the data and tooling that delivered them"}],"technologies":["VB.NET","SQL","SQL Server","XPath","VBA","Excel"],"displayDate":"Jan 2014 - Jul 2014"},{"id":"exp-business-ops-2013","company":"MaintenanceNet","title":"Business Operations Associate","type":"full-time","location":"Carlsbad, CA","remote":false,"startDate":"2013-06-01","endDate":"2014-01-01","description":"Acquired by Cisco · 2015","achievements":[{"id":"mnet-ops-1","description":"Owned AutoQuote campaign delivery and quality","impact":"while automating manual processes with VBA to cut errors and lift team efficiency — where the engineering started"},{"id":"mnet-ops-2","description":"Built .NET applications to retrieve and parse XML requests and report on campaign metrics","impact":"the first systems that turned an ops problem into a software one"}],"technologies":["VB.NET","SQL","SQL Server","VBA","Excel"],"displayDate":"Jun 2013 - Jan 2014"}],"contact":{"email":"contact@sl.huln.dev","github":"https://github.com/jhulndev","linkedin":"https://www.linkedin.com/in/jasonhuling"}}