Vetted AWS Professionals

“Asset Management Risk professional at Fidelity Investments who built and productionized an agentic RAG platform enabling compliance and analysts to query 10,000+ fund documents with cited answers in seconds. Implemented structure-aware semantic chunking (AWS Textract), hierarchical retrieval, and hybrid search to raise accuracy from 68% to 94%, and built an evaluation framework tracking accuracy/latency/cost/hallucinations—delivering 40+ hours/month saved and zero critical production failures.”

“Commercial UNIX specialist and former tech lead for a UNIX-based telco appliance spanning 11 SPARC Solaris servers, with strong Solaris troubleshooting (truss/iostat/netstat/snoop) and extensive shell scripting automation for safer, more consistent operations. Has executed multiple Solaris major-version migrations (6→8→10→11) and brings broad cross-UNIX platform experience (Solaris/SunOS/HP-UX/IRIX/OSF/1), while actively looking to deepen hands-on AIX/IBM Power expertise.”

“Backend engineer with healthcare-domain experience building a security-critical RBAC identity/authentication/authorization microservice suite used across hospital imaging platforms (X-Ray, Ultrasound, etc.). Demonstrates strong security mindset (mTLS, cert hygiene, JWT, pen-testing collaboration) and pragmatic scaling/reliability practices (Nginx load balancing, Redis caching, automated tests, canary rollouts).”

“Backend engineer with experience in both regulated healthcare and finance: built a multi-agent RAG system to generate FDA regulatory approval documents for biomedical devices, improving retrieval accuracy via hybrid search (semantic + BM25) and hierarchical chunking. Previously at JPMorgan Chase, led a Java microservice refactor and AWS migration using Elasticsearch-first patterns, caching, and safe rollout strategies (parallel runs, canary, blue-green) in asset/wealth management.”

“University robotics researcher graduating May 2026 who integrated an Intel RealSense D435i onto a TurtleBot3 (Jetson Nano) and built a ROS 2 node + OpenCV pipeline to feed color-based cues into navigation/path planning for RL grid-world experiments. Has hands-on ROS 2 experience spanning Gazebo simulation, Nav2, ros2_control, multi-robot namespacing, and ROS1-to-ROS2 bridging, plus CI/CD exposure (GitLab CI, Jenkins) from internships including aircraft navigation work.”