• Built and scaled core platform features using TypeScript and Next.js to support reinforcement learning environments and outcome verifiable task systems

• Developed internal tools to source, vet, and onboard domain experts efficiently for large scale human data projects in advanced science and other high value domains

• Implemented dynamic dashboards and workflow systems to manage operationally complex AI data pipelines

• Optimized server side rendering and application performance to support data intensive, research focused workloads

• Integrated APIs and backend services to power benchmarking systems used by frontier AI labs

• Contributed to internal tooling that supported the development of high difficulty reasoning benchmarks evaluated against frontier models

• Collaborated cross functionally with researchers, operators, and leadership to ship features in fast paced, high ownership environments

• Participated in architectural decisions to ensure scalability, reliability, and long term maintainability of the platform.

• Led the design and development of enterprise-grade applications using Python, React, and Node.js, ensuring seamless integration across distributed systems.

• Architected and deployed cloud-based solutions on AWS and GCP, utilizing services like ECS, Kubernetes, and Cloud Run for container management.

• Established robust CI/CD pipelines with GitHub Actions and AWS CodePipeline, enabling automated builds, testing, and deployments.

• Developed high-performance APIs (REST and GraphQL) to support real-time data processing and integrations with external services.

• Spearheaded the adoption of infrastructure-as-code (IaC) practices using Terraform, improving environment consistency and deployment efficiency.

• Mentored engineering teams on DevOps best practices, including monitoring, logging, and cost optimization in cloud environments.

• Delivered end-to-end solutions for client projects using Python (Django/Flask) and MERN stack, focusing on scalable backend services and React-based UIs.

• Automated deployment workflows by designing CI/CD pipelines with Jenkins and GitHub Actions, reducing deployment time and manual errors.

• Containerized applications using Docker and orchestrated scalable clusters via Kubernetes on AWS and GCP, improving system resilience.

• Built secure and scalable RESTful APIs to integrate third-party services and internal microservices.

• Migrated legacy monolithic systems to cloud-native architectures, leveraging AWS Lambda, Google Cloud Functions, and serverless frameworks.