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Vetted High Availability Professionals
Pre-screened and vetted.
Principal Full-Stack Software Engineer specializing in FinTech and Healthcare platforms
Mid-level .NET Full-Stack Developer specializing in FinTech and wealth management
Junior Software Engineer specializing in backend, systems, and applied ML
Senior DevOps/SRE Engineer specializing in multi-cloud Kubernetes and DevSecOps
Senior AIX/Linux Engineer specializing in IBM Power Systems, PowerVM, and High Availability
Mid-level Software Engineer in Test specializing in embedded and semiconductor equipment automation
Junior Backend Engineer specializing in distributed systems and platform reliability
Senior Backend Developer specializing in AWS-native Python systems and data workflows
Senior Hardware/QA Engineer specializing in enterprise servers, storage, and virtualization validation
Mid-level Backend Software Engineer specializing in Java microservices and Azure cloud
Senior Azure DevOps / SRE Engineer specializing in cloud infrastructure automation
Junior Software Engineer specializing in backend systems, QA automation, and AI/ML
Chandini Sattineni
Mid-level Software Engineer specializing in full-stack web, Go microservices, and AI integrations
“Backend/LLM engineer who ships production internal tooling end-to-end: automated data-request processing with monitoring-driven improvements (better error diagnostics and lower latency via query/index tuning). Also built a RAG-based internal Q&A system over company docs and operational logs with guardrails (similarity thresholds, fallbacks, response limits) and an eval loop using real user queries and human review to drive prompt/retrieval changes.”
Atharva Pandkar
Junior AI/ML Engineer specializing in LLM agents and RAG systems
“Built and deployed a production, multi-tenant modular agentic AI platform at Easybee AI, using LangChain/LangGraph with Redis-backed durable state to make agents reusable, traceable, and auditable. Emphasizes reliability via strict tool schemas, deterministic controllers, tenant-level policy enforcement, and regression testing derived from real production failures; also delivered AI automation for legal/finance workflows (attorney draw and expense automation) with explainable, deterministic payouts.”