Teams at Egen

Leads and mentors application engineers while designing Java and Spring Boot microservices. Oversees application modernization, VM-to-container migration, GCP and GKE deployments, Kubernetes troubleshooting, CI/CD, testing, database integration, observability, and distributed systems. Coordinates technical dependencies across a large application portfolio and collaborates with platform, DevOps, security, and architecture teams. Uses AI-assisted engineering tools to accelerate development, modernization, testing, documentation, and automation.

Designs and maintains Azure enterprise data infrastructure using Terraform and CI/CD pipelines. Implements multi-plane architectures, hybrid Azure-Google Cloud networking, secure platform services, Kubernetes workloads, identity and access controls, and centralized monitoring. The role supports Airflow, Milvus, Neo4j, GPU workloads, and healthcare-compliant environments with HIPAA, PHI, encryption, data residency, and secure SDLC requirements.

Build and operate distributed GPU training platforms for foundation models. Run and debug multi-node PyTorch and Ray Train workloads, tune GPU networking and scheduling, profile performance, and develop benchmarks and evaluation harnesses. Partner with infrastructure teams and client scientists to improve throughput, reliability, cost efficiency, observability, and end-to-end training pipelines on GKE.