Vetted Spring Boot Professionals

“Backend engineer with experience at HSBC and Machinations who has delivered major production performance wins (cutting large trade-file upload times from ~13–15s to ~2s) using chunked parallel processing with strong reliability controls. Also built and shipped an applied AI RAG workflow using Langflow + Cohere embeddings + FAISS with hosted/local LLM fallbacks (Hugging Face, Ollama) and production-grade guardrails, observability, and evaluation.”

“AI engineer who shipped a production chat assistant for a storage company by building the underlying RAG-style knowledge base (document ingestion, chunking/embeddings, FAISS vector store) and an admin update interface to keep content current. Also has full-stack delivery experience (Python REST APIs + React/TypeScript UI) and AWS operations using Terraform/Jenkins, including handling a real production performance incident by optimizing DB queries and adding auto-scaling.”

“AI/ML engineer who built a production RAG-based internal document intelligence assistant (LangChain + Pinecone) to let employees query enterprise reports in natural language. Demonstrated hands-on pipeline orchestration with Apache Airflow and tackled real production issues like retrieval grounding and latency using tuning, caching, and token optimization, while partnering closely with non-technical business stakeholders through iterative demos.”

“Full-stack/backend engineer with deep experience building real-time fraud and credit-risk systems. Shipped an event-driven fraud monitoring platform (Kafka→MongoDB/Redis→WebSockets) delivering sub-200ms updates to 3000+ concurrent internal users, and built a Java/Spring Boot credit risk decisioning API that improved turnaround time by 30–40%. Strong AWS production operations (ECS Fargate/RDS/Redis) with proven incident response and performance tuning.”

“LLM/agent workflow engineer with production experience at T-Mobile, focused on scalable agent architecture and robust real-time evaluation/monitoring pipelines. Partnered closely with marketing and product to automate customer engagement and other business workflows, translating AI capabilities into measurable KPI impact via dashboards and continuous performance tracking.”

“Full-stack engineer who has shipped and owned production analytics dashboards using Next.js App Router + TypeScript, combining server components for data-heavy pages with client components for interactive charts/filters. Also built a Temporal-orchestrated payment reconciliation workflow with versioning, idempotency, and exponential-backoff retries, and has hands-on Postgres query/index optimization using EXPLAIN ANALYZE.”

“Entry-level software engineer who has shipped end-to-end product features in a chat application, including a frontend table component plus backend support, then refactored the implementation after client feedback by switching UI libraries. Has production experience combining traditional NLP with an LLM fallback based on confidence thresholds for intent/entity extraction, and is building infrastructure around legacy enterprise APIs (MCP tools) including asynchronous job queues for long-running tasks.”

“Software engineer with experience at Goldman Sachs and Arizona State University’s Learning Engineering Institute, shipping production backend systems including a vendor equities invoice-generation service designed for extensibility across multiple vendors. Built Django REST + PostgreSQL backends with JWT auth and Pytest coverage, and delivered data-heavy, responsive Angular dashboards; also has exposure to AWS EC2 deployments and GitLab CI/CD automation.”

“New-grad/early-career engineer who led high-stakes modernization of a field-operations platform from Firebase to AWS using an incremental/dual-write strategy, achieving zero downtime and ~30–32% infra cost reduction while improving scalability. Also built and productionized an AI-native code assistant (LangChain + Pinecone RAG) with measurable online metrics and safety guardrails, and has experience working directly with CEO/CTO/CPO and embedded with customer teams to ship enterprise features quickly.”

“Backend/API engineer with ~4 years experience building production services in .NET Core/PostgreSQL/Redis/Docker and optimizing real-world latency issues (claims ~60% response-time improvement). Also built and owned an end-to-end RAG-based AI assistant using Python/FastAPI, OpenAI APIs, and Pinecone, plus agentic workflows with reliability guardrails (retries, confidence thresholds, monitoring). Currently pursuing a master’s degree and targeting a $150k base salary.”

“Software engineer/QA automation leader with Lowe’s experience owning automation quality strategy for a customer-facing platform supporting large contractor orders. Built TypeScript/React dashboards backed by Spring Boot microservices (MongoDB) and RabbitMQ async messaging, with strong CI/CD test automation and production monitoring (Prometheus/Grafana). Also created an internal automated test reporting dashboard that improved QA workflow through training-led adoption and iterative refinement.”