Ian David Rossi

About Ian David Rossi

AI & LLM Consulting + DevOps TransformationWe help startups as well as enterprises design, ship, and operate production-grade AI—LLM apps, RAG, and agents—without compromising reliability, security, or cost control. We also provide DevOps transformation services, developer experience, and microservices platform expertise. I work directly with C-level executives, core development teams, operations teams, and product management teams. Clients include Bose Corporation, Target Corporation, Johnson & Johnson, Harvard Business School, Verizon, Intel, and Enterprise Rent-A-Car.We love to: Deliver real AI features (RAG, agents, copilots) with evaluation, observability, and LLMOps Continuously deliver microservices Advocate for, facilitate, and create DevOps culture Containerize and continuously deliver applications to the cloud Build cloud-native, custom software delivery platforms on Kubernetes Mentor and train others in the aboveSelected accomplishments: Driven company-wide DevOps transformations from the top down, working directly with C-level executives Designed and built a custom cloud-native platform (containers, Kubernetes, Jenkins, and custom tooling) to deliver polyglot microservices Designed and built continuously delivered infrastructures for Fortune 500 and startups alike, including one supporting TPS from global locations (~50M tx/day) Designed and built highly available private OpenStack clouds Designed and built automated infrastructures using Chef, Puppet, Ansible, Sensu, Terraform, and AWS CloudFormationI’ve provided microservices architecture and DevOps consulting across the big data, financial services, national retail, manufacturing, medical, education, and software development industries for 20 years—and now bring that same engineering rigor to AI initiatives, from prototype to production.Learn more:

Experience

1. Senior Data Engineer at Chan Zuckerberg Initiative

   Aimtheory

   Feb 2025 — Present

   Support platform engineering for AI‑driven biomedical research workloads in a shared, multi‑tenant Kubernetes environment.Build and maintain platform tooling and workflows for GPU‑accelerated Kubernetes clusters supporting model training, inference, and scientific compute.Develop secure, reproducible research environments using containerization, JupyterHub, and workflow automation.Implement Retrieval‑Augmented Generation (RAG) pipelines using vector databases and curated internal data sources to support research assistants and knowledge discovery.Design and support multi‑agent workflows using LangChain and LangGraph for experiment orchestration, automation, and internal tooling.Integrate with existing GPU scheduling solutions (Run.ai) to support fair‑share access, quotas, and workload prioritization.Establish guardrails for data access, model usage, and cost visibility in shared AI platforms.Contribute GitOps workflows using Terraform and ArgoCD across multi‑cloud environments.Enhance observability using Prometheus, Grafana, Loki, Tempo, and distributed tracing.Technologies: Kubernetes, Docker, Terraform, ArgoCD, GitHub Actions, Python, Go, LangChain, LangGraph, Vector Databases, Run.ai, AWS, GCP, Helm, Istio

Education

• American School

  High School

  1992 — 1996

Skills

• Cloud Computing
• Crm
• Php
• Databases
• Open Source
• Windows Server
• Javascript
• Ruby
• Vmware
• Online Advertising
• Vmware Esx
• Webmaster Services
• Website Building
• Hyper-V
• Process Improvement
• Drupal
• Sales Process
• Social Media Marketing
• Virtualization
• Information Architecture
• Ubuntu
• Hadoop
• Mysql
• Project Management
• Online Marketing
• Tcp/Ip
• Dns
• Digital Strategy
• Vsphere
• Chef
• Centos
• Openstack
• Software Project Management
• Continuous Delivery
• IT Infrastructure Operations
• Linux System Administration
• Rackspace Cloud
• Amazon Ec2
• Vmware Server
• Cloud Applications