• Own strategy and implementation for hosting .NET, Python, Node.js, and React applications on AWS using Infrastructure-as-Code (Terraform). • Automate AWS infrastructure and optimize for scalability, observability, and cost. • Support SDLC deployments across all environments through production. • Manage and migrate data stores (Postgres, SQL Server, Oracle) to cloud-native AWS solutions. • Lead tooling improvements for modern CI/CD pipelines. • Prioritize timelines and deliverables across the engineering ecosystem. • Mentor and coach team members while fostering a collaborative DevOps culture. • Partner with engineering and product leaders to analyze requirements and deliver high-quality solutions.

• Design and implement scalable, secure, and resilient cloud-native applications using Azure Service. • Design and manage Azure Data Lake environments for large-scale data ingestion, processing, and analytics. • Design and implement CI/CD pipelines using Azure DevOps, GitHub Actions, or Jenkins • Develop and deploy cloud applications using Azure services like App Services, Functions, AKS, and Logic Apps • Automate infrastructure provisioning with tools like Terraform, ARM templates, or Bicep • Monitor and optimize cloud environments using Azure Monitor, Application Insights, and Log Analytics • Collaborate with development and operations teams to streamline release cycles and improve system reliability • Troubleshoot and resolve issues in cloud infrastructure and application deployments

• Own end-to-end deployment, publishing, and configuration for iOS and Android mobile applications • Manage App Store Connect and Google Play Console workflows, including signing, provisioning, and compliance • Automate mobile build and release processes to improve consistency and reduce manual effort • Coordinate closely with Engineering, Product, and Professional Services teams to ensure smooth releases • Design, build, and maintain Ansible automation for deployments, APIs, IIS configuration, certificate rotation, and environment standardization • Use Terraform to provision and manage infrastructure in a repeatable, auditable manner • Reduce configuration drift by establishing infrastructure-as-code as the source of truth • Create reusable automation patterns that support both mobile and backend systems • Operate and tune IIS in Windows-based production environments, including performance optimization and safe restarts • Support containerized workloads (Docker/Kubernetes) and help guide their adoption as part of the platform’s future state • Contribute to CI/CD pipeline improvements that support reliable, predictable deployments

• Design, operate, and scale GPU and CPU clusters for ML training and inference (Slurm, Kubernetes, autoscaling, queueing, quota management). • Automate infrastructure provisioning and configuration using infrastructure‑as‑code (Terraform, CloudFormation, cluster‑tooling) and configuration management. • Build and maintain robust ML pipelines (data ingestion, training, evaluation, deployment) with strong guarantees around reproducibility, traceability, and rollback. • Implement and evolve ML‑centric CI/CD: testing, packaging, deployment of models and services. • Own monitoring, logging, and alerting across training and serving: GPU/CPU utilization, latency, throughput, failures, and data/model drift (Grafana, Prometheus, Loki, CloudWatch). • Work with terabyte‑scale datasets and the associated storage, networking, and performance challenges. • Partner closely with ML engineers and researchers to productionize their work, translating experimental setups into robust, scalable systems. • Participate in on‑call rotation for critical ML infrastructure and lead incident response and post‑mortems when things break.