Vetted Confluence Professionals

“QA automation engineer with experience at Amazon Game Studios owning an end-to-end automated scale testing suite that simulates high-concurrency gameplay and captures performance telemetry. Improved coverage by bypassing hours of gameplay via programmatic state setup, enabling repeatable 4000-player dungeon-entry tests that exposed a messaging-queue bottleneck fixed before release. Also built maintainable Selenium/pytest UI automation with CI gating, reporting, and flake-reduction patterns.”

“Backend engineer who has led major platform evolution to cloud-native microservices (Spring Boot on AWS with Terraform) and built scalable, secure FastAPI APIs. Demonstrates strong production rigor with metric-driven validation, canary/phased rollouts, and incremental migrations using shadow traffic/feature flags/parallel writes—achieving faster deployments, fewer incidents, and zero-downtime traffic spikes and migrations.”

“Backend-focused Python/Flask engineer who has built authentication/profile services with clean modular architecture (blueprints + service layer) and tuned SQLAlchemy/Postgres for scale using indexing, query rewrites, and pagination. Has production-style integration experience for AI/ML via TensorFlow Serving and OpenAI APIs (batching, rate limiting, caching), plus multi-tenant data isolation and high-throughput background processing with Celery/Redis and idempotent jobs.”

“Machine learning/NLP engineer who built a production-oriented retrieval-based AI system at Morgan Stanley for healthcare use cases, combining RAG over unstructured patient records with deep-learning medical image segmentation (U-Net/Mask R-CNN). Strong in end-to-end pipelines and MLOps (Spark/MongoDB, AWS SageMaker, CI/CD, monitoring, automated retraining) and in entity resolution/data quality validation for noisy clinical data.”

“Software engineer in the mortgage/financial services domain (Freddie Mac) who builds end-to-end loan origination and credit risk capabilities using Spring Boot microservices, Angular dashboards, and data pipelines. Delivered measurable impact (30% reduction in underwriting turnaround time) and emphasizes production reliability/compliance with strong guardrails, observability, and evaluation loops for risk scoring systems.”

“Engineering leader/player-coach who led a high-stakes 0→1 in-house usage-based billing/rating platform to replace a third-party system, saving millions and protecting 30M+ in revenue. Deep experience in event-driven microservices on AWS (Lambda/SQS/DynamoDB), billing correctness, migrations, and incident response, while scaling teams through hiring, coaching, and lightweight execution processes.”

“GenAI/ML engineer with production experience building multilingual LLM systems (English/Spanish) and RAG-based clinical documentation summarization at Walgreens, combining prompt engineering, structured output validation, and rigorous evaluation (ROUGE + pharmacist review). Also orchestrated end-to-end ML pipelines for demand forecasting using Apache Airflow, PySpark, and MLflow with scheduled retraining and production monitoring.”

“Modes/progression designer on EA College Football (Dynasty and Road to Glory) who has owned multiple shipped progression systems, including recruiting and Road to Glory progression (meters, in-game reward triggers, and a "coach trust" meta-progression). Focused on modular system design and tuning/balancing for player-facing challenges and rewards, with strong QA-driven iteration and Blueprint-based prototyping practices.”

“AIX/IBM Power Systems engineer with hands-on production incident leadership in a regulated banking environment, using deep OS-level tooling to diagnose CPU entitlement and memory pressure issues. Experienced with HMC/vHMC, VIOS, and zero-downtime DLPAR resizing, plus PowerHA/HACMP clustering and validated failover testing. Also drives migration readiness via Bash/Python automation (60% manual-effort reduction) and phased AIX cloud/hybrid cutovers.”

“Robotics-focused candidate with multiple university robotics projects (MTE 380, MTE 544) and ROS 2 (Humble/Galactic) experience spanning perception, navigation, and simulation. Built a vision-based line-following and retrieval robot using HSV filtering and homography, and debugged real-time PID overshoot issues via timestamping/rate-limiting. Comfortable with distributed ROS 2 architectures (Python perception + C++ control), DDS/QoS, Gazebo testing, and Dockerized deployment.”

“Built and shipped a production LLM/RAG risk-case summarization and triage system used by fraud/compliance analysts, with strong grounding controls (evidence-cited outputs and refusal on low confidence). Demonstrates end-to-end ownership across retrieval quality, Airflow-orchestrated indexing pipelines, and compliance-grade privacy (PII redaction, RBAC, encrypted redacted logging, and auditable prompt/model versioning) plus a tight feedback loop with non-technical domain experts.”

“Software engineer with hands-on experience improving performance and reliability in financial workflows (settlements/loan processing), spanning React/TypeScript and Angular frontends plus Spring Boot microservices. Has delivered measurable latency improvements using PostgreSQL optimization and Redis caching, and has operated Kafka-based systems at scale with idempotent processing and backoff/retry strategies while iterating internal ops tooling with support/finance teams.”

“Software engineer/product-focused builder who has delivered customer-facing dashboards (React/TypeScript + Spring Boot) and microservices using RabbitMQ, emphasizing safe, fast iteration with CI/CD, feature flags, and monitoring. Also built an internal monitoring/reporting tool adopted by ops/support by involving users early and iterating based on feedback.”

“Built and owned major parts of a real-time distributed AI fraud-detection pipeline (ingestion, inference microservice integration, and automated action layer), optimizing latency and observability and reducing false positives by ~35%. Understands ROS/ROS2 concepts (nodes/topics/services) and planned hands-on ramp-up via ROS2 pub/sub exercises and Gazebo simulation, but has not worked on physical robots or ROS in production.”

“Software engineer working on an e-commerce platform, currently building a RAG-based recommendation system with a team new to the technology. Has delivered an end-to-end React/TypeScript website for a local car dealer and built an internal "encryption as a service" tool to secure sensitive data across repositories and through release/UAT, with experience debugging microservices integration issues.”

“Built and deployed an AWS-based LLM/RAG ticket triage and knowledge retrieval system (Pinecone/FAISS + Step Functions + MLflow) that cut support resolution time by 20%. Demonstrates strong production focus on hallucination reduction, PII security, and low-latency orchestration, with measurable evaluation improvements (e.g., ~25% grounding accuracy gain via re-ranking) and proven collaboration with support operations stakeholders.”

“Backend-leaning full-stack engineer who has shipped real-time, customer-facing dashboards and ticketing/payment features at Freshworks and Global Payments. Strong in Python API design (Django/Flask/FastAPI) and React/TypeScript UIs, with hands-on experience scaling PostgreSQL for high transaction volumes and operating services on AWS, including incident response and HIPAA-aligned security controls.”

“QA professional with Apple experience supporting the macOS Sonoma release, owning daily monitoring of submissions, crashes, regressions, and release verification across multiple OS/device builds. Notably isolated a memory-related issue in the Safari suite that caused an 18-hour build backlog and 156+ test crashes, leading to a Python-script fix that restored build times to ~1 hour and helped keep the release on schedule.”

“Game QA professional with ~10 years in the SDLC and deep live-service experience, including owning QA for Destiny 2's Guardian Ranks progression system across multiple seasonal iterations. Experienced coordinating outsourced QA, building risk-based test coverage plans, and driving bug triage/verification loops end-to-end to protect player experience and sentiment.”

“QA/automation engineer with experience at Riot Games’ player platform, owning E2E automation for mission-critical authentication/account flows using Playwright/JavaScript plus API automation. Built CI merge gates and nightly verification with Slack reporting, and repeatedly caught backend-driven session/authorization regressions before production. Known for stabilizing flaky UI tests via selector strategy and network intercepts, and for influencing design early with testability hooks and telemetry.”

“Full-stack engineer with production ownership across React/TypeScript, Node/Express, and Postgres, including zero-downtime releases and rollbackable migrations. Demonstrated measurable performance wins (20% response-time reduction) through DB query profiling and batching, plus hands-on AWS operations (ECS/Lambda/CloudWatch) and reliability patterns for ETL (retries, DLQs, idempotency). Experience shipping microservices quickly in ambiguous, fast-paced environments (Deloitte).”

“Full-stack engineer with recent JPMorgan experience building GPT-4-powered customer sentiment/feedback analytics products (Next.js 14 App Router + FastAPI + Postgres) and owning them post-launch with CloudWatch/Datadog observability. Also implemented Temporal-based transaction reconciliation workflows with strong reliability patterns (idempotency, retries, DLQ, versioning) and has prior high-scale healthcare dashboard experience at Optum.”

“Gameplay/systems designer who owned the end-to-end gameplay redesign of Top Spin 4 (2011)—including player states, ball physics, shot resolution, attributes, and AI—with much of that work later reused in TopSpin 2K25 (2024). Deep experience balancing realism and responsiveness for competitive multiplayer/online play, using extensive playtesting plus telemetry analysis (Tableau) to tune timing windows and core mechanics.”