Andres Gonzalez

Refactored existing infrastructure deployments from CloudFormation, Atmos, and manual provisioning to Terraform modules. Included modules for EKS, EKS Addons, Cognito, API Gateway, and networking (VPCs, subnets, peering, etc.). Implemented a policy as code framework (Cloud Custodian) that was used to identify and remediate insecurely deployed resources (e.g., public access S3 buckets) as well as cost management (e.g., deleting unattached EBS volumes). Set up the CI/CD infrastructure required to run GitHub Actions with private runners hosted on EKS. Established CI/CD deployment pipelines within GitLab to deploy infrastructure in AWS. Creating reusable GitHub Actions workflows for building and pushing various application container images and pushing to a container registry (ECR, Artifactory). Deploying containerised workloads to multiple container hosting platforms on AWS (Elastic Kubernetes Service, Elastic Container Service, Lambda). Involved with designing and developing an internal developer platform (IDP) using the Backstage framework.

Helped deliver multiple proof-of-value projects utilizing emerging technologies such as generative AI, machine learning, retrieval augmented generation (RAG), and multi-agent collaborative tasks. Handled the architecture design of multi-account innovation environments in AWS and Azure for rapid prototyping with services across both clouds, such as Azure Data and AI services, Amazon EKS, AWS ECS, API Gateway, RDS, and EC2. Provided technical oversight; oversaw technical aspects of the cloud and DevOps platform, ensuring we kept our internal customers at the forefront when building cloud and DevOps capabilities. Led the establishment and implementation of DevOps practices across the organization. Delivered a working MVP DevOps platform that met business and downstream project needs. Tooling included Terraform Enterprise, Hashicorp Vault Enterprise, GitLab, Sonatype Nexus Repo, and Prisma Cloud. Infrastructure design a retrieval augmented generation (RAG) application. The application summarised large documents 200+ pages into a few paragraphs (~ 200 words) extracting key insights and reducing a previously manual process from weeks to hours. Worked on multiple GenAI use cases that leveraged the internally built RAG capability. Did some exploratory work on building agentic-based applications using various agentic frameworks (LangChain, LangFlow, Azure AI Studio). Containerised the internally built RAG application (React front end, Spring Boot back end) and deployed to Amazon Elastic Container Service (ECS).

Designed patterns to provision and operate cloud data infrastructure services in Azure. These services include Azure Data Lake Storage Gen2, the Azure Synapse suite, Azure Machine Learning, Azure SQL, Azure Cognitive Services, and Microsoft Purview. Led infrastructure engineering squads of 4 to 10 engineers working on endorsed pattern automation and creating reusable Terraform modules for cloud infrastructure. All modules that were developed met security, risk, and operational requirements. Presented technical designs in various design forums to gain endorsements that allowed them to be consumable across the bank.

Established CI/CD pipelines for deploying applications onto Heroku (development staging and production) . Tooling used: GitHub Actions and Heroku Pipelines. Designed and implemented monitoring and alerts across the whole application stack. Leveraged tools such as New Relic, CloudWatch alarms, Sentry, and Logtail. This was a critical capability that was required for the public launch. Developed load testing suites using Gatling that would simulate end-to-end user integrations so we could identify bottlenecks in our infrastructure and remediate them prior to the public launch.

Designed the cloud architecture for a prototype mobile app that will allow its users to register, create a profile, and track their progress across different categories. The GCP services used were Firebase, Cloud Functions, and Cloud Storage. Performed all the back-end development in Go, which primarily consisted of writing Cloud Functions that would perform actions based on user activity. The tech stack included React Native, Redux, GitHub, and GitHub Actions. Tracked and managed the development of the MVP for the project through GitHub and GitHub Issues.

Developed dashboards using Tableau and Plotly Dash to visualize cloud spend. These dashboards were used to identify optimization opportunities, which would then turn into automation jobs (Lambda and ECR tasks) to fix or clean up resources. Created ETL pipelines to extract data from diverse data sources (API, SQL databases, and flat files) that fed a Redshift data warehouse used to build analytics jobs and other automation. The pipelines were written in both Python and Go. Designed and built a Django-based data center asset management system. This system was used to track all physical infrastructure across many data centers. Assisted in the development of a serverless data archiving solution, moving terabytes of data from on-prem Oracle databases to a cloud-native solution and dramatically lowering operating costs. Used technologies such as S3, Python, Glue, and Athena. Provided consulting to engineering teams during the solution design phase to provide cost-effective solutions to cloud infrastructure requirements. Built various REST API endpoints to publish aggregated data views from the data collected through the ETL pipelines by leveraging Django, Flask, and Go (Gorilla Mux). This data is used to set financial budgets, forecasting, and cost optimization.

Led the DevOps/infrastructure team, working closely with the engineering and product management teams to deliver customer features in a rapid, tested, and secure manner. Automated the creation and tear down of the cloud infrastructure used by our engineering teams. By doing so, we ensured the infrastructure was maintained as code, was repeatable, and torn down when not required. Reduced cloud OPEX spending by 15% per month. This was achieved by automating environment creation and tear down, right sizing and decommissioning legacy systems, and purchasing reserved capacity at lower rates. Created CI/CD pipelines containerizing applications across multiple frameworks (Node.js, Scala, Java, and .NET). These services were deployed to a self-hosted Docker server and Elastic Container Service in AWS.

Led a team based out of Sydney responsible for delivering projects that added new capacity or increased existing capacity of the AWS Edge network throughout Asia–Pacific (APAC). Collaborated with other regional counterparts to create a streamlined project delivery process, which reduced the time in which these projects were delivered. Designed a custom high-density cabling solution with a fiber manufacturer, which allowed a much higher density of fiber optic cable to be provisioned at a lower cost and a faster installation time.

Managed all internal IT infrastructure for the company, including physical end-user devices, network infrastructure, telephony systems, and virtualized hosting environments. Managed data center relocation projects for infrastructure supporting internal systems as well as customer-hosted applications. Migrated all applications and services running on bare metal servers to virtualized environments running on VMware Vsphere.