mohammedpatla

Maintained highly available blockchain infrastructure, consistently achieving 99%+ uptime across multiple client networks by enforcing robust reliability and operational best practices. Designed and managed infrastructure orchestration using Nomad and Consul, enabling resilient service discovery, efficient workload scheduling, and scalable deployments. Implemented comprehensive observability and alerting frameworks leveraging Zabbix, SigNoz, and PagerDuty, significantly improving proactive monitoring, incident detection, and response effectiveness. Administered secure secrets and cryptographic key management using Vault, strengthening platform security, compliance, and protection of sensitive assets. Operated and optimized bare-metal and dedicated cloud environments, ensuring high-performance, secure, and compliant infrastructure for public blockchain workloads.

Led backend and infrastructure engineering initiatives, leveraging NestJS, Terraform, and Docker to deliver end-to-end platform development from architectural planning through production deployment. Secured and operated validator infrastructure across multiple blockchain networks, safeguarding environments managing $20M+ in Total Value Locked (TVL) while meeting strict reliability and security standards. Deployed and managed Proof-of-Stake (PoS) nodes on SGX-enabled bare-metal infrastructure, enhancing execution security, performance isolation, and trust guarantees. Achieved ~50% infrastructure cost reduction by strategically migrating services from AWS EC2 to ECS, optimizing resource utilization without compromising performance or availability.

Managed and integrated core AWS services including IoT, EC2, and RDS, supporting scalable application and device infrastructure across production environments. Optimized application and device performance by enhancing front-end responsiveness and IoT firmware feedback loops, improving system reliability and maintainability. Led a strategic database migration from PostgreSQL to MongoDB, delivering 2× faster write performance and significantly reducing front-end resource consumption.

Developed and delivered production-grade applications using Vue.js, contributing to a facial recognition platform deployed for Law Enforcement Agencies with high reliability and usability standards. Improved recognition accuracy and processing efficiency by enhancing machine learning models through parallel computing, working closely with research teams. Customized and optimized Lambda server environments with tenserflow to deploy high-performance AI models, ensuring scalable, stable, and reliable client-facing solutions.