AVP - Technology Lead, Deutsche Bank (GCP-based Kubernetes Trading Platform and Data-Risk Controls)
Duration: Aug. 2024 - Present
Summary: Developed and maintained a Google Cloud Platform Kubernetes environment supporting trading workflows, including a retrieval-augmented agent powered by Vertex AI and Gemini to provide natural-language access to platform data. The project focuses on enhancing trading and customer-facing systems with strong IAM, KMS, and VPC Service Controls aligned with bank policies.
Responsibilities:
- Built a retrieval-augmented agent on Vertex AI and Gemini for a trading platform, giving traders and support engineers natural-language access to platform data instead of manual lookups.
- Owns platform architecture decisions for GKE-based services underpinning trading workflows, working with security and risk teams to keep IAM, KMS, and VPC Service Controls aligned with bank policy.
- Runs GitOps delivery through ArgoCD across multiple GKE clusters, cutting manual deployment steps and giving engineering
- teams a consistent path to production.
- Wired OpenTelemetry tracing into core services and paired it with Cloud Monitoring dashboards so incident response starts with data instead of guesswork.
- Sits on architecture review, weighing new service designs against security, cost, and operational risk before they reach production.
- Coordinated a customer-facing migration workstream onto GCP, working across engineering and compliance to keep data-residency and audit requirements intact.
- Cut recurring GCP spend by right-sizing overprovisioned GKE node pools and tightening autoscaling policies.
- Mentors junior engineers on IaC and Kubernetes fundamentals, reviewing Terraform modules before they touch production.
- Rolled out OPA/Gatekeeper policies across the cluster fleet to catch misconfigured workloads before they ship.
- Traced a recurring Cloud Build pipeline failure to a stale Artifact Registry permission, fixed it, and documented the fix for the wider platform team.
- Reviews third-party and vendor tooling against the bank's security and data-risk requirements before it gets added to the stack.
- Presents architecture and risk tradeoffs to internal technology governance forums, translating platform decisions into terms non-technical stakeholders can act on.
Technologies: Google Cloud Platform (GCP), Kubernetes (GKE), Vertex AI, Gemini, Retrieval-Augmented Generation (RAG), IAM, KMS, VPC Service Controls, ArgoCD, OpenTelemetry, Cloud Monitoring, OPA/Gatekeeper, Terraform.
Senior Site Reliability Engineer, Lululemon Athletica Inc. (EKS-based E-commerce Platform SRE Practice)
Duration: Feb. 2022 - Aug. 2024
Summary: Led the Site Reliability Engineering practice for a fleet of Amazon EKS clusters supporting Lululemon's e-commerce platform. The project aimed to improve platform reliability, security, and deployment efficiency while managing cost and compliance during migration and peak shopping seasons.
Responsibilities:
- Ran the SRE practice for a fleet of EKS clusters supporting the e-commerce platform, owning SLOs and error budgets across a dozen-plus services.
- Rebuilt CI/CD around GitHub Actions and ArgoCD, moving teams off a slower Jenkins pipeline and cutting release lead time.
- Hardened IAM and Secrets Manager policies ahead of a security audit, closing gaps flagged by the risk team.
- Tuned autoscaling and right-sized EC2/EKS node groups, trimming idle compute spend without touching peak-season headroom.
- Owned the on-call rotation for core platform services. Cut pages meaningfully over two quarters by fixing root causes instead of clearing alerts.
- Wired OpenTelemetry and Datadog SLO dashboards into the incident process, sharpening on-call triage.
- Worked alongside data and compliance teams on migration planning ahead of a system move, keeping change windows tight and auditable.
- Rolled out Falco for runtime security monitoring across EKS, catching a handful of misconfigured containers before they became incidents.
- Stood up Terraform Cloud workspaces to replace scattered local state files, giving the platform team a single source of truth for infrastructure changes.
- Configured AWS WAF and GuardDuty alerting for customer-facing services, tightening the edge ahead of peak shopping season.
- Paired with application engineers on Crossplane-based self-service provisioning, cutting the wait time for new environment requests.
- Piloted Firecracker microVMs for a lightweight, fast-boot internal workload, evaluating cold-start and isolation tradeoffs against standard EC2/EKS pods.
Technologies: Amazon EKS, Kubernetes, GitHub Actions, ArgoCD, IAM, AWS Secrets Manager, EC2, OpenTelemetry, Datadog, Falco, Terraform Cloud, AWS WAF, AWS GuardDuty, Crossplane, Firecracker microVMs.
Senior DevOps Engineer, University of Phoenix (EKS Platform Migration and Observability Enhancement)
Duration: Jan. 2019 - Feb. 2022
Summary: Led migration from legacy Jenkins pipelines to GitHub Actions and ArgoCD for GitOps deployments on Amazon EKS. Standardized infrastructure with Terraform modules and enhanced platform observability with Prometheus, Grafana, ELK, and Datadog. Supported remote operations scaling and security improvements during the COVID-19 pandemic.
Responsibilities:
- Migrated legacy Jenkins pipelines to GitHub Actions once it went GA, then layered ArgoCD on top for GitOps-style deploys to EKS.
- Built out Terraform modules for a growing EKS footprint, standardizing VPC and IAM patterns across environments.
- Supported the shift to full remote operations in 2020, scaling monitoring and on-call coverage as traffic patterns changed overnight.
- Owned Prometheus and Grafana for platform observability, adding ELK for log correlation once incident volume made manual grepping impractical.
- Paired with application teams to move services onto Helm 3 charts, replacing hand-rolled deploy scripts.
- Dug into recurring EKS node failures traced to a misconfigured autoscaler, fixed the config, and wrote the runbook so it didn't recur.
- Ran AWS CodePipeline for legacy workloads still waiting on their GitHub Actions migration, keeping both paths stable during the transition.
- Rolled out basic OpenTelemetry instrumentation on a handful of core services once the tooling matured, closing gaps in the existing Prometheus setup.
- Set up Datadog dashboards for a handful of customer-facing services, giving support teams visibility they didn't have before.
- Tore down a legacy Helm 2 tiller setup during the Helm 3 migration, closing a longstanding cluster-wide permissions risk.
- Trained newer engineers on the team's Terraform and Kubernetes conventions as the platform team grew through the pandemic hiring push.
Technologies: Amazon EKS, Kubernetes, Jenkins, GitHub Actions, ArgoCD, Terraform, Prometheus, Grafana, ELK Stack, Helm 3, AWS CodePipeline, OpenTelemetry, Datadog.
AWS DevOps Engineer, Nationwide Insurance (Kubernetes Cluster and Infrastructure Automation)
Duration: Sep. 2017 - Dec. 2018
Summary: Built and maintained a self-managed Kubernetes cluster on EC2 instances, automating infrastructure provisioning and monitoring. Improved deployment pipelines and containerized legacy Java services to enhance development and production parity.
Responsibilities:
- Built Jenkins pipelines for a self-managed Kubernetes cluster running on EC2, handling image builds, Nexus artifact publishing, and deploys.
- Wrote early Terraform and CloudFormation templates to replace manual AWS provisioning for VPC, IAM, and RDS.
- Set up Prometheus and Grafana monitoring for a platform that previously relied on Nagios.
- Worked with the infra team on Ansible playbooks for config management across a growing EC2 fleet.
- Containerized a handful of legacy Java services with Docker, cutting the gap between local dev and production environments.
- Wired SNS and SQS into a batch processing workflow, replacing a cron job that had been quietly failing for weeks.
- Patched and upgraded the self-managed Kubernetes control plane during a scheduled maintenance window, with zero unplanned downtime.
- Paired with the DBA team on RDS backup and restore testing, catching a gap in the existing disaster-recovery plan.
- Ran Maven builds and Nexus artifact promotion for a handful of internal Java services ahead of each release.
- Documented the team's Terraform and Jenkins conventions, giving new hires an onboarding path that hadn't existed before.
Technologies: Kubernetes, EC2, Jenkins, Terraform, CloudFormation, Prometheus, Grafana, Ansible, Docker, SNS, SQS, RDS, Maven, Nexus.
Software/Build Engineer, Ernst & Young (Internal Tooling Build Automation and CI Migration)
Duration: Jun. 2014 - Aug. 2015
Summary: Automated build and deployment processes for internal applications, migrating source control from SVN to Git and establishing CI conventions. Improved build efficiency and reduced manual deployment errors.
Responsibilities:
- Set up and maintained Jenkins build jobs for internal tooling, one of the team's first moves toward automated builds.
- Wrote Shell and Python scripts to replace manual deployment steps for a handful of internal applications.
- Migrated a legacy codebase from SVN to Git and helped the team adjust to the new branching workflow.
- Ran Maven builds for a handful of internal Java tools, fixing dependency conflicts as they came up.
- Kept basic Linux servers patched and monitored for a small internal application fleet.
- Paired with senior engineers to document the team's first CI conventions, ahead of onboarding two new hires.
- Fixed a recurring Jenkins job failure traced to a stale credential, cutting a source of weekly manual reruns.
- Held informal walkthroughs for junior teammates on Git basics as the team moved off SVN.
- Traced a slow build pipeline to an unnecessary full recompile step and cut it out.
- Broke down a manual release checklist into a handful of scripted steps, closing gaps that had caused missed steps before.
Technologies: Jenkins, Shell scripting, Python, SVN, Git, Maven, Linux.
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