Vetted AWS Professionals

“Meta engineer who owned end-to-end production systems for AI-enabled smart glasses, spanning React/TypeScript apps through Node/Java microservices on AWS EKS with Kafka/Postgres. Built and productionized a real-time RAG pipeline (LangChain + OpenAI + Elasticsearch) with rigorous guardrails (shadow/canary, fallbacks, monitoring), delivering major improvements in latency (~35–40%), error reduction (~30%), and engagement (reported +40% DAU).”

“Backend/platform engineer who has owned real-time reporting and streaming analytics systems end-to-end, combining FastAPI/Postgres APIs with Kafka consumers, Celery background jobs, and Redis caching. Strong DevOps/GitOps experience deploying Python/Node microservices to AWS EKS with Helm, ArgoCD/FluxCD, and CI pipelines, and has supported phased on-prem to AWS migrations using Terraform and traffic cutovers.”

“Software development manager who led development of the open-source AI agents framework Strands (for Amazon Bedrock), which launched mid-year and is used as a primary agent-development framework at Amazon and externally. Owned the Strands SDK end-to-end, drove adoption through stakeholder management and agile execution, and led a JavaScript-to-TypeScript migration to improve type safety and maintainability.”

“Engineering leader who drove Lightroom Mobile’s roadmap at Adobe by enforcing reuse of Photoshop imaging tech to deliver RAW, non-destructive mobile editing with full Creative Cloud compatibility. In startup environments, has repeatedly scaled and professionalized engineering orgs (career ladders, evaluation systems, delivery process) and led high-stakes cloud/platform transformations—migrating off Heroku and consolidating fragmented AWS/GCP usage into a single GCP platform—improving reliability, deploy speed, and cutting cloud costs by 20%+.”

“LLM/agent engineer who built a production code-generation agent at Corvic AI that lets non-technical users query CSV/tabular data in natural language by generating and executing Python. Focused on making LLM systems reliable and scalable via schema-aware validation, sandboxed execution-feedback retries, prompt caching/embeddings, async execution, and high-throughput data processing with Polars; also partnered with Adobe product/marketing to ship brand-aligned AI content generation for email and push notifications.”

“Banking/credit-union technology executive (CTO/CTIO) who has led modernization and product delivery through major change, including a post-merger roadmap that helped grow a credit union from $600M to $1.5B in 3 years. Hands-on leader who drove cloud microservices/API architecture, introduced CI/CD, and accelerated releases from quarterly to weekly while scaling teams and operating effectively with distributed/remote orgs.”

“Hands-on engineering leader with early-stage startup experience who balances coding with executive alignment and delegation. Has delivered offline-capable SaaS mobile demos under tight timelines, built monetization-ready mobile architectures (dynamic cloud assets + in-app purchases), and increased product velocity via component-based game architecture plus stakeholder self-serve tooling.”

“Robotics software engineer with hands-on ROS 2 experience who helped build an autonomous 5-DOF robotic arm that plays Backgammon, owning perception (OpenCV) and game-logic while adding robustness features like lighting tolerance and auto-calibration. Also worked on a Raspberry Pi/LiDAR car project, improving mapping accuracy through data-logged calibration and contributing to multi-robot collision-avoidance coordination via a server-based pub/sub system.”

“Built and deployed a production LLM conversational AI system at OpenAI supporting chat, summarization, and semantic search at 1M+ requests/day, driving major latency (40%) and accuracy (25%) improvements through Pinecone optimization and tighter RAG with re-ranking. Also has Amazon experience improving recommendation systems by translating ML metrics into business terms to boost CTR and conversions, with strong MLOps/orchestration depth (Airflow, MLflow, SageMaker, Kubeflow).”

“ML engineer with 5 years at Stripe building and productionizing real-time fraud detection at massive scale (3M+ transactions/day; $5B+ annual payment volume). Delivered measurable impact (22% accuracy lift, 18% loss reduction, +3–5% authorization rates) and has strong MLOps/orchestration experience (Docker, Kubernetes, Airflow, MLflow, CI/CD, monitoring/rollback) plus a structured approach to LLM agent/RAG evaluation.”

“IBM Power/AIX infrastructure engineer who has owned large-scale Power9/AIX 7.x estates across primary/DR (VIOS/HMC/vHMC) and has deep hands-on experience with DLPAR, shared processor pool governance, and PowerHA recovery. Also brings modern DevOps/IaC capability—built Azure DevOps/GitHub CI/CD for Terraform + Kubernetes/Helm with strong security controls and resolved a production Terraform state-lock failure by redesigning backend locking and pipeline concurrency.”