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Vetted Containerization Professionals
Pre-screened and vetted.
Mid-Level Full-Stack .NET Engineer specializing in cloud, APIs, and data analytics
Mid-Level Software Engineer specializing in cloud microservices and AI automation
Senior Cloud & DevOps Engineer specializing in AWS migration, IaC, and CI/CD
Mid-level Full-Stack Engineer specializing in Java/Spring Boot microservices and React
Mid-level Generative AI Engineer specializing in LLMs, RAG, and NLP systems
Junior Software Engineer specializing in ML inference infrastructure
Junior Full-Stack Software Engineer specializing in backend, cloud, and AI systems
Junior Full-Stack Software Engineer specializing in cloud, distributed systems, and AI
Senior Software Engineer specializing in backend systems, data pipelines, and AI solutions
Senior Frontend React Developer specializing in scalable web applications
Mid-level DevOps/Cloud Engineer specializing in CI/CD, IaC, and Kubernetes on AWS/Azure
Senior Full-Stack/Backend Engineer specializing in distributed systems and cloud-native platforms
Anupriya Palanisamy
Mid-Level Software Engineer specializing in Java microservices and event-driven systems
“Backend-focused engineer with experience spanning research and healthcare: owned a Python/SQL data pipeline that transformed vulnerability-fix code data from SQLite into model-ready JSON for LLM analysis. Also deployed Dockerized Spring Boot microservices to Kubernetes with Jenkins CI/CD and built Kafka-based real-time event streaming (appointment/report events) with idempotent consumers to avoid duplicate processing.”
Balakrishna Mylapilli
Mid-level AIML Engineer specializing in production ML and MLOps
“ML practitioner who built a production customer risk scoring system to replace slow manual approvals, owning the full pipeline from feature engineering and XGBoost training to deploying a Dockerized FastAPI prediction service. Emphasizes reliability and business-aligned evaluation (recall/ROC-AUC, threshold tuning, drift monitoring) and is comfortable translating model decisions into stakeholder metrics like conversion rate (experience at EasyBee AI).”
Kevin Thomas
Intern Software Engineer specializing in AI, cloud, and backend systems
“Candidate has internship and graduate-project experience building AI agents, including a production log-analysis assistant using a lightweight agentic/RAG-style workflow with local GPT training and validation against historical logs. They also worked on Android/iOS game build and release processes in a Unity-based robot racing game environment, and highlight measurable LLM outcomes including 80% analysis accuracy, 2-5 second latency, and 50% cost reduction.”