Vetted Confluence Professionals

“Built and deployed a production LLM-powered RAG assistant for healthcare teams (care managers/support) to answer questions from clinical and policy documentation, emphasizing trustworthiness via improved retrieval, reranking, and strict grounding prompts to reduce hallucinations. Also has hands-on orchestration experience with Apache Airflow for end-to-end ETL/ML workflows and applies rigorous testing/metrics (hallucination rate, tool-call accuracy, latency, cost) to ensure reliable AI agent behavior.”

“Backend/data engineer focused on production-grade Python microservices and AWS platforms, including a hybrid Lambda + ECS Fargate architecture managed with Terraform and CI/CD. Has hands-on reliability experience (JWT/OAuth, timeouts, retries, centralized error classification) and built AWS Glue/PySpark ETL pipelines consolidating PostgreSQL/RDS, MongoDB, and S3 sources into curated partitioned Parquet datasets. Demonstrated measurable SQL tuning impact (8 minutes to 25 seconds) and disciplined legacy-to-modern migrations with parity validation and UAT sign-off.”

“Early-career engineer from BNP Paribas who drove a large-scale observability modernization—selecting and implementing Prometheus/Grafana for a 2000+ server estate, then productionizing it on Kubernetes via Docker/Jenkins. Known for hands-on demos, strong documentation/templates, and pragmatic troubleshooting (including custom Python metrics) that improved visibility and cut debugging time by ~60%.”

“Full-stack engineer who has owned customer-facing and internal web portals end-to-end (API, database, React UI, and deployment). Experienced designing multi-service architectures with Node/Express and Java/Spring Boot plus RabbitMQ/Kafka messaging, emphasizing contract/versioning discipline, observability, and operational tooling that measurably reduces support load and manual work.”

“Software engineer/product owner experience at UnitedHealth Group owning a high-volume claims eligibility console end-to-end (React/TypeScript + Spring Boot microservices) processing 1M+ transactions/day. Strong in event-driven architecture (Kafka/RabbitMQ), HIPAA-aligned security (OAuth/JWT/RBAC), and building internal observability tools that improve incident triage and production reliability.”

“Built and deployed a production clinical claim validation RAG system at GE HealthCare that automated nurses’ patient-history/claims checks, cutting manual review time by ~65%. Designed the full stack (retrieval, embeddings, Pinecone, prompt/verification guardrails, FastAPI backend) with PHI-compliant anonymization via NER and orchestrated pipelines using Airflow, Azure ML Pipelines, and MLflow with drift monitoring.”

“Built a production "appeals co-pilot" for a healthcare claims appeals team, combining an XGBoost/logistic ranking model with a Python/LangChain RAG stack (FAISS + Mistral 7B) to surface high-probability appeal wins and speed policy-grounded drafting. Emphasizes reliability and trust: hybrid retrieval with metadata routing, citation/eval scripts, guardrails, and an explainability layer that non-technical stakeholders could understand and override.”

“Applied ML/embodied AI practitioner who built an on-device gesture-control system for smart-home lights using Raspberry Pi + camera, focusing on privacy-preserving real-time inference and hardware-constrained optimization (async pipeline + TF Lite INT8). Also made a high-impact architecture decision for an ML content evaluation/QA pipeline processing millions of annotated text samples weekly, reducing batch runtime from ~6 hours to ~40 minutes while lowering compute cost.”

“Data/ML practitioner with experience at UnitedHealth Group building a fraud claims detection solution combining structured claims data and unstructured notes, validated with compliance stakeholders to improve actionable accuracy. Also applied embeddings, vector databases, and fine-tuned language models in a Bank of America capstone to detect threats/anomalies in financial documents, with production-minded Python ETL workflows using Airflow.”

“Backend-leaning full-stack engineer who has shipped production-critical data/reporting features at Walmart and built an end-to-end workflow automation product (FastAPI + React/TypeScript + PostgreSQL) deployed on AWS. Strong in performance/reliability engineering (parallel ETL, batch DB operations, indexing via EXPLAIN ANALYZE), secure API design (JWT/RBAC), and pragmatic incident-driven scaling (separating workers from API layer).”

“Gameplay engineer with shipped experience (Just Cause 4) and strong systems ownership in C++/Unreal Engine 5, including a loot spawning/loot table pipeline optimized through profiling-driven memory copy elimination and validated via custom simulation tools. Also built a server-authoritative fast travel system in a proprietary engine, handling multi-player/vehicle spawn coordination with client-side collision checks and latency testing across NYC and Stockholm.”

“QA/project leader with ~19 years experience running high-profile, multi-million-dollar software initiatives and driving quality through disciplined milestone gates (Alpha/Beta/FC/GM), regression planning, and weekly bug scrubs. JIRA-centric practitioner (Zephyr/Confluence) who partners closely with engineering, automation, documentation, marketing, and sustaining teams—including offshore collaboration—to unblock testers and improve diagnostics for difficult issues like memory leaks.”

“QA/automation engineer with hands-on experience spanning web UI automation (Cypress/JavaScript) and hardware/firmware validation (BIOS/BMC, FPGA). Has delivered high-impact reliability and throughput improvements in server/HPC environments, including automation that enabled booting across ~250 servers and requirement clarification that unblocked firmware work for ~550 servers.”

“Data engineer with Charter Communications experience modernizing large-scale AWS data lake pipelines: ingesting S3 data, validating against legacy systems, transforming with PySpark/Spark SQL, and serving via Iceberg/Delta tables. Worked at 50M–300M record scale, delivered >99.5% data match, and built monitoring/alerting (CloudWatch/SNS) plus retry orchestration (Step Functions) and data quality gates (Great Expectations).”

“Backend/full-stack engineer who has owned production retail and order/inventory systems end-to-end, using Spring Boot microservices with Kafka event-driven workflows. Strong in production correctness patterns (idempotency, retries/DLQs, schema versioning) plus observability (Prometheus/Grafana) and developer-facing API design (Swagger, OAuth2/JWT, versioning/deprecation). Also built TypeScript/React SPAs and cited ~40% UI performance improvement.”

“Game tester with hands-on QA experience primarily on mobile and PC titles, looking to transition into console testing. Emphasizes critical-path prioritization (e.g., crashes) and uses AI-driven R&D to ramp quickly while reviewing test cases and masking sensitive data.”

“Game-studio QA tester with full lifecycle experience (feature kickoff through release/live updates), strong in structured test planning, edge-case discovery, and disciplined defect tracking. Partners closely with engineers via Jira/standups, providing detailed repro steps, logs, and evidence, and builds regression coverage to prevent recurring UI/data-loss issues.”