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Vetted gRPC Professionals
Pre-screened and vetted.
Mid-level Software Engineer specializing in distributed systems and full-stack web applications
Software Engineer specializing in distributed systems, cloud cost optimization, and AI/ML
Senior Full-Stack Engineer specializing in event-driven systems for FinTech and Healthcare
Senior Full-Stack Software Engineer specializing in Healthcare IT and cloud-native systems
Senior Backend Engineer specializing in cloud-native microservices and real-time streaming
Staff Software Engineer specializing in full-stack platforms and cloud-native microservices
Mid-level Full-Stack Software Engineer specializing in microservices and cloud-native systems
Mid-level AI Data Engineer specializing in real-time streaming and LLM-powered fraud analytics
Mid-Level Software Engineer specializing in backend microservices and cloud-native ML platforms
Senior Software Engineer specializing in distributed systems and cloud-native microservices
Senior Software Engineer specializing in Healthcare IT and cloud-native microservices
Senior AI/ML Engineer specializing in Generative AI and conversational systems
Senior Backend Software Engineer specializing in FinTech and distributed systems
Senior Systems Engineer specializing in distributed ML infrastructure
Senior Software Engineer specializing in cloud platforms and real-time collaboration
Mid-level Software Engineer specializing in cloud API authorization and distributed backend systems
Senior Software Engineer specializing in distributed systems and agentic AI platforms
Executive IT & Software Development Leader specializing in cloud-native transformation and trading platforms
Mid-level Full-Stack Developer specializing in cloud-native FinTech and Healthcare IT
Mid-level Software Engineer specializing in distributed systems and data platforms
Devisri Veeramachaneni
Senior Software Engineer specializing in cloud backend systems and LLM-powered agents
“Amazon Fire TV Devices engineer who built and shipped a production LLM-powered lab triage and validation system that grounds recommendations in internal runbooks/known-issue data and pushes evidence-based actions via dashboards and Slack. Emphasizes safety and measurability with structured JSON outputs, replay-based evaluation on historical incidents, and production metrics (e.g., disagreement rate and time-to-first-action), plus cost/latency optimizations like caching, batching, and rule-based fast paths.”
Vyas Cholayil
Mid-Level Software Engineer specializing in Python automation, DevOps, and microservices
“Backend-focused engineer who built an internal wiki LLM chatbot end-to-end using FastAPI, Kubernetes, and ChromaDB vector search, including frontend integration. Also has strong DevOps/migration experience—automating large work-item and repo migrations (Jira/FogBugz/ADO on-prem to cloud) via Python scripts, JSON mappings, REST APIs, and validation test suites.”