Hi, I'm Tam Nguyen, a platform and infrastructure engineer with a focus on building systems that scale.

I've spent the last 15+ years designing, automating, and securing cloud and on-premise infrastructure at companies like Microsoft, Amazon, and high-growth startups.

I specialize in solving technical problems hands-on, whether it’s reducing cloud spend, improving reliability, or automating infrastructure at scale. Along the way, I’ve also guided teams and mentored engineers, ensuring that the work we do makes a meaningful impact.

Experience

Associate Director, Network Engineering
Vitech Systems Group, 2023 - 2025

  • Led network engineering teams in developing and maintaining network roadmaps, designing solutions, managing projects, directing operations, and analyzing key infrastructure metrics

  • Owned PagerDuty onboarding, escalation workflows, and alert tuning for global network security team

  • Conducted technical reviews of firewall, VPN, and routing configurations to close security gaps and align with HIPAA and SOC-2 requirements

  • Redesigned and implemented a new AWS VPC endpoint strategy, resulting in a $300K annual reduction in data transfer and NAT Gateway costs

  • Partner with the Finance team to handle network expense allocation, forecasting, cost analysis, and reporting, and reduce department’s spend forecast by 30% in 2025

Platform Technical Lead Manager
Microsoft, 2019 - 2023

  • Led Platform team that consisted of 3 pods: infrastructure (Ansible, Terraform, etc.), developer experience (CI/CD, graphs/alerts, etc.), and cloud operations (SOC-2, pen test, etc.)

  • Partnered with cross-functional product managers, client managers, and engineering teams to create a comprehensive process checklist for client onboarding

  • Conducted 1-1 meetings with team members to manage deadlines, provided mentoring, while maintaining deep technical involvement

  • Migrated a high-volume, low-latency Java application from virtual machines to Azure Kubernetes Service for more than 30 customers in retail

  • Built and rolled out an AtlantisCI CI/CD pipeline for Terraform repositories, enabling team-wide self-service infrastructure deployments and reducing bottlenecks

Senior Infrastructure Engineer
PromoteIQ, 2017 - 2019

  • Built and led a 10-person Platform/Infrastructure team from a Series A ad-tech startup to Microsoft acquisition

  • Participated in managing engineering teams with tasks such as planning, scheduling, and interviewing/hiring

  • Developed and launched various client-saving features for a high-volume, low-latency API that generates over $300MM/year in revenue

  • Automated the build process, supported and managed a distributed data pipeline that provided up to over 100,000 events/sec with self-hosted RabbitMQ and Elasticsearch clusters

  • Utilized Ansible to develop a cloud-agnostic tool that provisioned and configured Adserver VM infrastructure that collocated with retailers’ global data centers.

Earlier Roles
Amazon/Quidsi, eChalk, TRC Healthcare, etc.

  • Migrated on-prem workloads to AWS.

  • Designed CI/CD pipelines for 500+ servers.

  • Built dashboards and monitoring systems to improve visibility and reliability

Notable Skills & Projects

Core Expertise:

  • Cloud: AWS (expert), Azure, GCP (basic), VPCs, Transit Gateway, VPN, IAM, RBAC

  • Infra-as-Code: Terraform, Ansible, GitOps, Atlantis CI, CloudFormation (basic)

  • Containers: Docker, Kubernetes (AKS), Helm

  • Monitoring/Logging: Prometheus, Grafana, ELK, CloudWatch, Zabbix, PagerDuty

  • Languages: Python, Bash, YAML, HCL

  • Other: PostgreSQL, MySQL, Redshift, RabbitMQ, Kafka, Hadoop, Jenkins, Airflow, Jira, Agile, SLO/SLI design

Notable Projects:

  • Cut $300K/year in AWS costs by redesigning VPC strategy.

  • Automated infrastructure for high-volume APIs generating $300M+ revenue annually.

  • Rolled out an AtlantisCI CI/CD pipeline for Terraform repositories, enabling team-wide self-service infrastructure deployments.

Education

  • University of California, Davis
    Bachelor of Science, Computer Science