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Vetted Spring Boot Professionals
Pre-screened and vetted.
Mid-level Full-Stack Engineer specializing in AI agent infrastructure
Junior Software Engineer specializing in backend systems and cloud infrastructure
Senior Software Engineer specializing in full-stack systems and cloud platforms
Senior Software Engineer specializing in distributed systems and agentic AI
Entry-level Software Engineer specializing in backend systems and AI platforms
Junior Software Engineer specializing in AI-powered backend and distributed systems
Mid-level Full-Stack Engineer specializing in e-commerce platforms
Senior Software Engineer specializing in cloud-native full-stack and distributed systems
Senior Full-Stack Engineer specializing in FinTech and scalable web platforms
Mid-level Full-Stack Software Engineer specializing in enterprise platforms and AI
Mid-level Java Developer specializing in microservices for financial services
Punith Jayaramu
Mid-Level Full-Stack Software Engineer specializing in FinTech and Mortgage systems
“Full-stack engineer with deep AWS serverless and reliability experience in fintech/underwriting systems, including eligibility scoring and dynamic rule deployments. Built and productionized an LLM-powered incident RCA assistant (Bedrock Claude 3 + custom RAG + React) achieving 92% precision and ~75% MTTR reduction, with mature guardrails (evals, drift monitoring, HITL, audit logs) and strong operational rigor (canaries, chaos testing, DLQ remediation).”
Mid-level Full-Stack Engineer specializing in cloud-native Java microservices
“Software engineer using AI pragmatically to accelerate development while keeping human review central to quality. Has hands-on experience applying AI and lightweight multi-agent workflows in a microservices environment spanning Java Spring Boot APIs, React modules, and Kafka event flows, with strong emphasis on architecture validation and production safeguards.”
Jyothiraditya Madina
Mid-level Full-Stack Developer specializing in FinTech and Healthcare IT
“Candidate has hands-on experience at Cognizant building production-grade automation and integration solutions across Python ML services, Java microservices, Kafka, and Selenium-based UI testing. They stand out for a strong reliability mindset—covering failure modes, observability, flaky test hardening, and translating ambiguous payment-system business processes into resilient end-to-end automated workflows.”
Shamala Chandrappa
Mid-level AI Engineer specializing in agentic AI, LLM systems, and healthcare AI
“Healthcare-focused ML/AI engineer who has built production voice agents and clinical question-answering systems end-to-end, from experimentation through deployment, observability, and iteration. Particularly strong in making LLM systems reliable in real workflows via RAG, fine-tuning, guardrails, evaluation pipelines, and shared Python tooling; cites ~20% clinical QA accuracy gains and ~40% faster physician decision turnaround.”