Vetted Java Professionals

“Full-stack engineer who built and iterated a CRM dashboard at ReplyQuick by sitting with end users, prioritizing blockers, and shipping frequent updates—improving usability and performance enough to replace a spreadsheet workflow within ~2 months. Demonstrates strong security fundamentals (OAuth2/JWT + RBAC) and practical microservices experience (decoupling a CRM API from a PDF-processing service via async processing and status tracking).”

“Built and deployed a production NLP sentiment analysis system at Piper Sandler to turn noisy, finance-specific customer feedback into scalable insights. Demonstrates strong end-to-end MLOps: fine-tuning BERT, improving label quality, monitoring for language drift, and automating retraining/deployment with Airflow and Docker (plus Kubeflow exposure).”

“Built a production LLM-powered clinical note summarization and retrieval system that structures patient/provider/payer discussions into standardized outputs (symptoms, treatments, clinical codes, and prior-auth decisions) and stores notes as embeddings for hybrid search and proactive prior-authorization prediction. Experienced with LangChain/LangGraph orchestration, RAG, and grounding against medical code databases, and has communicated model feasibility/limitations to business stakeholders (Virtusa/Comcast).”

“Backend/Node.js-focused engineer who improved a widely used shared config/logging utility library by fixing a real-world async race condition (single disk read under concurrency) and adding stronger validation/testing, resulting in more deterministic services and faster startup/build/CI times. Also builds internal platform automation spanning Python/Go/TypeScript with strong documentation practices and security-conscious customer onboarding (e.g., sensitive Kubernetes clusters, HashiCorp Vault access issues).”

“ML/NLP engineer with Industrial IoT experience who built an end-to-end anomaly detection and GenAI explanation system: AWS (S3, PySpark, EC2/Lambda) pipelines feeding dashboards, plus transformer-embedding vector search to connect anomalies to noisy maintenance notes and past events. Demonstrated measurable impact (15% lift in defect detection; ~35% reduction in manual review; 35% fewer preprocessing errors) and strong productionization practices (orchestration, monitoring, rollback, data-quality controls).”

“AWS Cloud DevOps Engineer focused on production Linux environments, building secure CI/CD pipelines (Jenkins/GitHub) to deploy Dockerized services to AWS ECS and automating infrastructure with Terraform/CloudFormation. Strong in operational troubleshooting and scaling (CloudWatch-driven performance remediation, Auto Scaling/ELB, multi-AZ HA patterns), but explicitly does not have IBM Power/AIX or PowerHA/HACMP experience.”

“Product/UX designer who built a cloud-based data management and visualization system for healthcare and manufacturing, translating script-driven and highly technical workflows into guided, step-based experiences. Strong in progressive disclosure, role-based defaults, and trust-building UI patterns, with hands-on prototyping in Figma and close design-engineering collaboration (HTML/CSS, component systems, working TypeScript familiarity) to ship scalable, accessible designs.”

“Software engineer/product-minded builder who owns customer-facing products end-to-end and ships in 1–2 week increments using CI/CD, automated testing, and feature flags. Built a TypeScript/React/Node platform that cut page load times by 40% and scaled to 3x concurrent users, and designed RabbitMQ-based microservices with Prometheus/Grafana monitoring. Also delivered an internal real-time support analytics dashboard that reduced response times by 30%.”

“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.”

“Backend/data platform engineer who owned an enterprise Django REST + PostgreSQL reporting backend and built Python ETL pipelines to normalize 3M+ legacy customer records, improving data reliability by 85%. Strong Kubernetes/GitOps practitioner (Helm, ArgoCD, Jenkins/GitHub Actions) with real-world production debugging experience, plus Kafka streaming at 5M events/day and a zero-downtime monolith-to-event-driven microservices migration on AWS that cut infra costs by 42%.”

“Full-stack product engineer who has shipped customer-facing features end-to-end, including a product detail page backed by Java/Spring Boot microservices and a React/TypeScript UI. Demonstrated measurable impact through performance and maintainability improvements (30% faster APIs, 25% less duplicated UI code, 40% reduced API complexity via GraphQL) and has operated/scaled apps on AWS with CI/CD, monitoring, and incident-driven scaling fixes.”

“Full-stack engineer who built a live-streaming edtech platform at KratosIQ, owning the entire frontend and the backend streaming layer. Notably migrated the system from a P2P mesh to an SFU architecture to handle scaling under heavy load, and delivered measurable React performance gains (450ms to 40ms render time) validated via Lighthouse and web vitals.”

“Lead developer on a Warner Brothers Discovery media management platform, building Python/Flask APIs and AWS-based workflows. Delivered a serverless search overhaul (Lambda + API Gateway + OpenSearch Serverless) while maintaining parity with legacy Rekognition tag-based search, and implemented event-driven ETL (SNS/SQS) to ingest/validate CSV metadata into PostgreSQL with strong logging and incident response practices.”