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Vetted Elastic Stack (ELK) Professionals
Pre-screened and vetted.
Mid-level Software Engineer specializing in full-stack, cloud, and AI systems
Senior Software Engineer specializing in cloud-native backend, ETL, and AI/ML on AWS
Mid-level Full-Stack Java Developer specializing in cloud-native microservices
Mid-level Full-Stack Software Engineer specializing in FinTech and cloud-native systems
Mid-level Full-Stack Developer specializing in AWS, Python/FastAPI, and React
Mid-level Software Engineer specializing in cloud-native microservices and ML-driven automation
Senior Full-Stack Software Engineer specializing in cloud microservices and GenAI
Mid-level Java Developer specializing in Spring Boot microservices (FinTech & Healthcare)
Mid-level Full-Stack Engineer specializing in Java microservices and FinTech
Senior Full-Stack Engineer specializing in FinTech and Healthcare IT
Principal Software Engineer specializing in distributed systems and cloud-native backend platforms
Senior Backend Engineer specializing in cloud-native microservices and secure APIs
Senior Technical Support Engineer specializing in cloud and container security
Mid-level Full-Stack Java Developer specializing in cloud-native AI platforms
Senior Full-Stack Engineer specializing in backend, cloud, and AI systems
Johnnie Sanders
Executive AI Architect specializing in enterprise cloud and FinTech solutions
“Candidate brings an operator-to-founder profile with leadership experience in IT and Business Systems and a strong grasp of how ideas become venture-backable products. They speak fluently about startup evaluation criteria such as TAM, technical defensibility, speed to scale, and AI differentiation, and appear especially motivated by building solutions end-to-end in startup or venture studio environments.”
Silpa Bhavani
Mid-level Full-Stack Java Developer specializing in cloud-native microservices
“Software engineer with strong compliance-domain experience who built a customer-facing compliance and reporting dashboard using React/TypeScript with Spring Boot microservices. Demonstrates mature production engineering practices—contract-first APIs, event-driven architecture (Kafka/RabbitMQ), caching (Redis), and robust CI/CD + observability (Prometheus/Grafana/ELK)—and also created a Python-based audit automation tool adopted into the standard release process.”
Navya Panyala
Senior Software Engineer specializing in identity, cloud-native microservices, and reactive web apps
“Product-focused full-stack engineer with Walmart and Dell experience who built and shipped a real-time engagement dashboard end-to-end (Kafka Streams, Spring Boot, React/TypeScript/D3) used daily by business teams, moving them from next-day reports to real-time decisioning. Strong in performance/reliability (Redis caching cut latency ~40%, 90%+ test coverage, Prometheus/CloudWatch monitoring) and production operations on AWS/EKS including handling a cascading failure from a memory leak with zero-downtime rollback and redeploy.”
Hitha Magadi Vijayanand
Mid-level Backend Software Engineer specializing in AWS cloud and FinTech platforms
“JP Morgan engineer and Texas A&M student web developer who has owned production systems end-to-end, including a real-time ML training workflow that improved internal search relevance by 30%. Experienced with AWS cloud migrations and operating containerized services on ECS with CloudWatch+ELK observability, Terraform infra, and Spinnaker CI/CD; also built event-driven pipelines with RabbitMQ and Elasticsearch at 1M+ record scale.”
Mithilesh Gaurihar
Mid-Level Software Engineer specializing in Java microservices and cloud-native systems
“Full-stack engineer (SAP Labs experience) who built an end-to-end, real-time fraud detection system on Java 11/Spring Boot microservices with Kafka event streaming and a React/Redux analytics dashboard with WebSocket updates. Demonstrated strong production ownership by diagnosing a critical memory leak with Prometheus/CloudWatch + heap dumps and improving performance with Redis caching (40% faster queries), while also modernizing deployments via Kubernetes, Jenkins CI/CD, and Terraform.”