
I build the platform that ML and data teams run on: they submit training, inference and data jobs through an API, and the platform schedules them as Ray and Spark workloads on Kubernetes, ships every change through GitOps, and provisions the AWS underneath as code.
Interface
Teams submit and track workloads
Orchestration
Pipelines, schedules and rollouts
Compute
Distributed training and inference
Runtime
Clusters, ingress and packaging
Foundation
Cloud, IaC and delivery
Platform APIs
FastAPI services that turn "run this job" into a tracked, scheduled workload.
Distributed compute
KubeRay on EKS running RayCluster, RayJob and RayService with autoscaling and GPUs.
GitOps delivery
Argo CD, release-please and GitHub Actions take every change from PR to cluster.
Infrastructure as code
Layered Terraform modules that onboard a service with IAM, DNS, storage and databases.
AI Platform Engineer building scalable systems with AWS, EKS, Kubernetes, Ray, and GitOps to enable reliable model training, inference, and application deployment at scale. Day to day I ship FastAPI services, KubeRay and Argo workloads on EKS, Terraform modules and GitHub Actions pipelines. I hold a Software Engineering degree from ISEP (Master's in progress) and thrive in diverse teams where collaboration, clear communication, and adaptability matter.
Internship focused on software engineering practices and development fundamentals.
Curricular internship: worked on a project developing applications with Microsoft Power Apps. The formative approach of the project accelerated my acquisition of platform knowledge, and the experience gave me an in-depth understanding of team dynamics and how to act effectively in a professional, formal environment.
Built a solid foundation across the various areas of Software Engineering, complemented by hands-on experience gained through numerous academic projects — spanning web development, databases, algorithms, and team collaboration.
Ongoing. Advancing expertise through specialized coursework in modern software engineering practices and industry-relevant technologies.
A few people who have worked with me — and what they say.
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Things I've built, synced straight from GitHub.
I'm always open to new opportunities, collaborations, or just a friendly chat about AI infrastructure, platform engineering, or software in general. Drop me a line!