Vetted Hibernate Professionals

“Backend/event-driven systems engineer who built an end-to-end “software robot” for AI-driven invoice processing: FastAPI ingestion + OCR integration + classification mapping, with strong emphasis on reliability (idempotency, retries) and scalability (background workers, event-driven architecture). Experienced in production-grade distributed systems tooling (Kafka, Docker/Kubernetes, GitHub Actions, ArgoCD) and real-time debugging via tracing/telemetry, and expects $10k–$12k/month.”

“Backend-focused engineer building customer support/order-tracking platforms with Java 17/Spring Boot microservices and a React/TypeScript frontend. Deep experience running event-driven systems on Kubernetes (Kafka, Redis, MySQL) with strong observability (Prometheus/Grafana/Splunk), SLOs, and safe deployment practices (feature flags, canaries). Also built an internal monitoring/debugging dashboard that consolidated metrics and logs for on-call engineers and was adopted by other teams to speed incident response.”

“Backend/platform engineer focused on high-traffic financial systems, owning real-time event-driven ingestion and Kafka streaming pipelines using Python/FastAPI, Avro schemas, and AWS services. Has hands-on Kubernetes (EKS) and GitOps/CI-CD experience (ArgoCD/Jenkins) and supported large-scale migrations from legacy VMs to containerized microservices with zero/low-downtime cutovers.”

“Backend/platform engineer who owned high-volume Java/Spring Boot microservices on AWS (Kafka + RDS/DynamoDB) and has hands-on experience debugging complex production latency incidents across DB, JVM/GC, and async consumers. Also shipped applied AI features for ops, including an LLM-powered log analysis assistant and an incident-response agent with strong safety guardrails (schema-validated tool use, retries/backoff, and human-in-the-loop escalation).”

“Backend/AI engineer at Intuit who built a production AI-powered case assistant for support agents (FastAPI on AWS EKS) combining Postgres case data, OpenSearch retrieval with embedding reranking, and internal LLMs. Improved peak-season reliability by diagnosing P95/P99 timeout spikes and cutting P95 latency from ~800ms to <400ms via composite indexing, keyset pagination, connection pool tuning, and caching, while adding grounded-generation guardrails (evidence packs, confidence thresholds, fallbacks, human-in-the-loop).”

“Frontend-focused JavaScript engineer who built Collabsync with real-time chat and file sharing using Socket.io, emphasizing reusable components, clear event contracts, and performance (minimizing React re-renders). Has experience at PwC building internal React/Angular dashboards and documenting insurance APIs, plus a contract role at Capital One delivering in fast-changing, loosely defined environments.”

“Built a production LLM-driven personalization microservice for realtor.com using LangChain/LangSmith with an MCP tool layer and RAG to generate schema-constrained ranked listings in real time, replacing a rule-based engine and improving engagement/lead conversion. Also owned an ambiguous cross-channel identity initiative, implementing an identity graph via Twilio Unify with required SDK and data-warehouse integration.”