Vetted Engineering Professionals in Maryland

“Backend/ML systems engineer who built a Flask + PostgreSQL internal ticketing platform and demonstrates strong database/ORM performance depth (indexes, partitioning, RLS multi-tenancy). Notably optimized a high-throughput attachment OCR/embedding pipeline with batching, deduplication, and Redis caching, cutting median latency from 45s to 10s and reducing worker cost by 35% while increasing throughput 4x.”

“Robotics Software Engineer with 2.5 years at the Army Research Lab building production tools and cloud infrastructure for large-scale ROS/Unity simulation on AWS. Created a Python GUI to streamline analysis of massive (100GB) ROS bag/MCAP datasets and has deep ROS2/Nav2 performance debugging experience (executor/QoS/TF tracing). Also built an in-house ROS perception pipeline for an assembly-line use case, reaching 92% accuracy.”

“Backend/platform engineer with hands-on ownership of Kubernetes GitOps delivery (GitHub Actions + Argo CD) on AWS EKS, including progressive rollouts and reliable rollback across interdependent microservices. Built a Python/FastAPI ML-driven document-processing service (PostgreSQL + S3) to complement existing Spring Boot systems, and implemented Kafka streaming pipelines with Schema Registry plus Prometheus/Grafana observability. Also supported a hybrid cloud-to-on-prem migration for compliance/latency with phased rollout and incremental PostgreSQL migration.”

“Production infrastructure engineer from Textron Systems who owned IBM Power/AIX 7.2 environments supporting manufacturing-critical automated RF test workloads. Deep hands-on experience with VIOS/HMC, DLPAR performance issues, SAN/vFC failures and failover recovery, plus modern DevOps practices (Azure DevOps CI/CD, Key Vault) and Terraform-based AWS infrastructure with remote state/locking and drift controls.”

“Backend engineer who built an AI-driven "Smart Feedback Analyzer" API (Flask → FastAPI) that processes user feedback with NLP (Hugging Face + OpenAI) and returns structured insights. Demonstrates strong production-minded architecture: stateless services, Cloud Run + Docker deployment, Redis/Celery background processing, and Postgres/SQLAlchemy performance tuning (EXPLAIN ANALYZE, indexing, N+1 fixes), plus multi-tenant data isolation via JWT/API-key derived tenant IDs.”