• Own secure deployment, reliability, performance, and cloud infrastructure for FDA-approved, AI-powered medical devices processing PHI in HIPAA, SOC 2, HITRUST, and FDA quality-controlled environments, partnering with SRE, AI, data, engineering, security, quality, and regulatory teams.
• Architected private-network SageMaker inference for a custom medical imaging foundation model that generates preliminary radiology report text from patient X-rays; secured 3 endpoints across 3 AWS accounts with PrivateLink, private subnets, no-egress security groups, fine-scoped Lambda invocation permissions, and KMS-encrypted ECR images.
• Productionized fine-tuned vLLM inference by packaging 100GB+ Docker images, publishing through GitHub Actions, and deploying isolated SageMaker model containers while removing public internet exposure for PHI-bearing inference traffic.
• Created first-of-kind AI coding-agent guardrails for Claude Code, GitHub Copilot, and Cursor in production Terraform and AWS Lambda repos, requiring read-only credentials, PR review, Atlantis delivery, and blocking secrets/PHI plus destructive Terraform and mutating AWS CLI actions.
• Built a GCP Dataflow pipeline to de-identify and catalog 1.67PB of medical images for AI training, removing DICOM metadata, burned-in PHI, and sensitive filenames while producing audit manifests, enforcing least-privilege worker IAM, using encrypted GCS, and running workers in private subnets; reduced run costs by ~75%.
• Provisioned secure 256-GPU NVIDIA H100 Slurm training infrastructure on GCP with private subnet isolation, firewall controls, encrypted access-controlled shared storage, access/job logging, and Terraform-managed infrastructure for production AI research workloads.
• Implemented GCP Workload Identity Federation for EKS-hosted Atlantis and Terraform deployments, avoiding long-lived service account keys, enforcing least-privilege cross-cloud role mappings, and introducing Terraform-based IaC management for GCP environments.
• Strengthened ML/cloud vulnerability and supply-chain security with AWS Inspector/ECR scans, Snyk, Trivy, Dependabot, Terraform/IaC scanning, CVE remediation, hardened AMIs/containers/EC2 instances, immutable patching pipelines, and SHA-pinned GitHub Actions.
• Applied AWS Bedrock Data Automation to extract text from image-based medical reports for downstream AI/analytics workflows, and led a Lambda-based inference initiative that improved scalability while reducing cost by 23% versus EC2.
• Created reusable Terraform modules adopted across 20+ AWS accounts to standardize CloudWatch dashboards, GitHub Actions OIDC federation, AWS Lambda infrastructure, and AWS Verified Access endpoints for the broader engineering organization.
• Led OIDC-based AWS authentication rollout across ~10 GitHub Actions repos, replacing stored AWS keys with short-lived federated credentials, repo/branch-restricted IAM trust policies, least-privilege access, branch protection, CODEOWNERS, required reviews, and separated Terraform plan/apply workflows.
• Implemented zero-trust access for sensitive internal applications using AWS Verified Access and Okta, replacing VPN-based access for Tableau and Terraform drift detection tools used by approximately 20–30 users.
• Built centralized observability, alerting, uptime dashboards, and incident runbooks for ~30 production systems across 3–4 teams using CloudWatch, Okta-secured access, and PagerDuty, improving incident visibility and MTTR.
• Supported security investigations by helping the security team locate and analyze relevant CloudWatch Insights, CloudTrail, AWS Security Hub, and production telemetry logs.
• Automated AWS operational workflows with Step Functions, Lambda, and Systems Manager for EC2 patching and production operations; extended Terraform CI/CD across AWS/GCP, modernized the EKS delivery platform to reduce cost by ~83%, and built immutable image pipelines for reliable releases and patch management.
• Installed and configured the PerformanceBridge radiology analytics platform and supporting systems across Linux and Windows Server environments for healthcare customers in multiple regions.
• Resolved complex customer concerns and technical issues through deep investigation, research, and reproduction.
• Automated recurring configuration tasks, created procedural documentation, and provided training to colleagues, improving operational consistency and onboarding.
• Supported product expansion into EMEA and APAC through client implementations and technical configuration for organizations including:
• Built high-performance cloud-based applications for biobanking and laboratory automation.
• Won employee Key Strategy award for contributions to COVID-19 projects.
• Streamlined COVID-19 testing and reporting workflows, increasing efficiency and reducing errors for global biobanking processes.
• Designed a sample lineage interface for the UK NHS COVID-19 system, enabling the processing of hundreds of thousands of tests per week.
• Developed a sample normalization workflow for Curative Korva Labs, which conducted 20% of all tests in California, and integrated with state and local public health departments for reporting results.
• Built Rails-based software for clients including Roche and the National Institutes of Health.
• Reduced sample turnaround times for multiple clients from weeks to hours.
• Designed integrations with hardware devices and external systems including:
• Designed and built analytics tools for the post-acute care industry.
• Built web scrapers to collect plan data from state health insurance exchanges.
• Rebuilt a Tableau-based product using open-source software and on-demand cloud solutions, lowering costs by 50%.
• Designed and developed a medical sample inventory application for an Android RFID reader.
• Integrated with hardware devices including: