Vetted Engineering Professionals in the Raleigh-Durham

“Backend/data engineer with aerospace telemetry and reporting experience across RTX and other orgs, spanning Python/FastAPI microservices, AWS serverless/containers, and AWS Glue-to-Redshift analytics pipelines. Has led legacy modernization with parallel-run parity validation and incremental rollout, and demonstrates strong operational ownership (monitoring, incident response, and cost optimization).”

“Backend engineer who evolved and migrated a real-time smartwatch telemetry ingestion/analytics platform in a healthcare context, focusing on reliability under poor network conditions. Experienced with Python/FastAPI and Java microservices, PostgreSQL performance tuning, and production-grade security (JWT/OAuth, RBAC, RLS) with incremental rollout and parallel-run migration strategies.”

“Software engineer who builds workflow-centric products end-to-end, including a customer-facing module on the Trident AI content platform and an internal content workflow tool adopted as the default process. Strong in TypeScript/React + FastAPI architectures and in scaling event-driven microservices with RabbitMQ, emphasizing reliability (idempotency, DLQs) and observability (correlation IDs) to reduce outages and debugging time.”

“Built and shipped "OnCall Copilot," a production Slack-based RAG assistant that answers on-call questions from runbooks and postmortems with citations using a FAISS vector index. Emphasizes reliability and measurable performance via strict guardrails ("no evidence, no answer"), evaluation metrics, drift monitoring, and operational hardening with Docker, logging, health checks, and offline fallback.”

“Backend engineer with experience modernizing legacy systems and building modular Python/Flask services, including a REST-to-GraphQL migration for an e-commerce platform that improved API response time by 45%. Strong in performance and scalability work across PostgreSQL/SQLAlchemy (indexing, JSONB, N+1 fixes, connection pooling) and high-throughput systems (Celery + Redis), plus integrating ML microservices with TorchServe, Kafka streaming, feature stores, and Prometheus/Grafana monitoring.”

“Built a Meta-style AI smart glasses system emphasizing on-device privacy and low-latency processing, spanning ESP32-S3/FreeRTOS firmware through an NVIDIA Jetson Linux edge-AI pipeline in Python/Docker. Strong in real-time streaming optimization (zero-copy GDMA, deterministic scheduling), encrypted transmission (AES-256), and reliability via stress testing and robust error handling; currently building CI/CD automation tests using Playwright and computer vision.”