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Vetted Amazon EKS Professionals
Pre-screened and vetted.
Mid-Level Full-Stack Software Engineer specializing in cloud integrations and real-time systems
Senior AWS DevOps Engineer specializing in cloud infrastructure and CI/CD automation
Senior Software Engineer specializing in backend, AWS cloud infrastructure, and data pipelines
Mid-Level Full-Stack Software Engineer specializing in GenAI and cloud-native systems
Senior Full-Stack Java Developer specializing in cloud-native microservices for FinTech
Junior Software Developer specializing in full-stack and data engineering
Intern AI/ML Engineer specializing in NLP, graph analytics, and agentic RAG systems
Senior Full-Stack & AI Engineer specializing in FinTech and Healthcare
Mid-level Full-Stack Developer specializing in modern web apps and cloud platforms
Mid-Level Software Engineer specializing in cloud microservices and AI automation
Mid-level DevOps/Cloud Engineer specializing in CI/CD, IaC, and Kubernetes on AWS/Azure
Senior Full-Stack Engineer specializing in Python, cloud-native SaaS, and data pipelines
Senior Full-Stack Developer specializing in automation, IoT, and integrations
Senior Java Developer specializing in cloud-native microservices and event-driven systems
Staff/Lead DevOps & Site Reliability Engineer specializing in cloud infrastructure and Kubernetes
Siva swathi javisetty
Mid-level Full-Stack & Cloud Engineer specializing in backend, AWS infrastructure, and DevOps
“IBM Power/AIX engineer who has owned a large production estate (20+ Power9/Power10 frames and 400+ LPARs) with vHMC and dual-VIOS HA. Has hands-on incident recovery experience (NPIV/RMC issues, LPM restores) and PowerHA failovers, plus modern DevOps exposure using Terraform on AWS and CI/CD with GitHub Actions/Jenkins (including deploying AI/RAG and vision workloads).”
Sana Khan
Mid-Level Software Developer specializing in cloud-native microservices, iOS, and ML deployment
“Backend engineer with production ERP experience deploying microservices and improving performance/reliability using a metrics-driven approach (logs, latency, error rates). Has hands-on cloud/hybrid operations across AWS and Azure with Docker/Kubernetes, and has resolved real-world mobile sync issues by tuning timeouts/retries and reducing payload sizes. Builds configurable Python services to deliver customer-specific behavior without destabilizing the core codebase.”
Lokeshwar Reddy Gummireddy
Mid-level Backend Engineer specializing in Python APIs, event-driven systems, and Kubernetes
“Backend Python engineer who owned a real-time manufacturing insights streaming service, building FastAPI async microservices with Kafka-style queue buffering, batching/backpressure, and a low-latency snapshot store. Led a serverless-to-Kubernetes (EKS) migration at UGenomeAi using GitOps-style GitHub Actions pipelines, standardized config/secrets, and improved deployment consistency with pinned dependencies and multi-stage Docker builds.”
AjayEshwar Venkatesan
Intern Network/Applied Engineer specializing in cloud security and Kubernetes
“Security-focused engineer with hands-on experience implementing and troubleshooting security tooling (including an open-source SIEM) and integrating SCA/container scanning into AWS/EKS and GitHub Actions pipelines. Demonstrates strong cloud security fundamentals (least-privilege IAM, IRSA, private subnet/VPC design, CloudTrail/GuardDuty) and can translate security-usability tradeoffs (e.g., password policy and 2FA) to different stakeholders.”
Dhairya Gajjar
Mid-Level Software Engineer specializing in Healthcare Data Platforms
“Backend/ML engineer with healthcare domain experience building secure Medicare/Medicaid data APIs and real-time patient risk scoring. Shipped an end-to-end ML pipeline (scikit-learn/XGBoost) served via SageMaker and integrated into Flask APIs, with strong production reliability practices (Kafka schema validation, regression replay, observability, drift monitoring, and human-in-the-loop guardrails).”