Vetted Encryption Professionals

“Backend/ML platform engineer who owns end-to-end delivery of ML-serving APIs (FastAPI + TensorFlow) and runs them reliably on Kubernetes using ArgoCD GitOps. Has hands-on experience solving production-only issues (probe tuning for model warm-up, resource profiling) and building scalable Kafka streaming pipelines, plus supporting phased on-prem to AWS migrations with dependency discovery and recreation of hidden jobs/workflows.”

“Exited Founder-CEO with deep-tech experience who raised capital and built a venture around making end-to-end encryption with cloud-level performance and data sovereignty feasible. Demonstrated first-principles technical rigor (network/TCP analysis) to prove scientific feasibility, then progressed from proof of concept to prototype and eventual exit, with a strong bias toward ultra-lean, customer-paid MVPs.”

“Entrepreneur/fintech product builder who raised a $100K pre-seed from ex-Google/Microsoft execs and built a real-time, direct-to-vendor bill pay micropayments platform. Previously helped scale Norton LifeLock to 1M users (2003) and also created Karma LA, a fraud-resistant, verified donation system (including VA veteran verification) aimed at improving trust and conversion in giving.”

“Backend engineer working on Plumas Bank’s digital modernization, building a FastAPI-based loan origination/processing system with OAuth2/JWT security, AWS Lambda-driven PDF document generation to S3, and MongoDB integration. Has led a legacy workflow migration to a new microservice using dual-write/dual-read and monitoring, and emphasizes multi-tenant isolation via layered API controls plus row-level security.”

“Backend engineer who has built end-to-end data and platform systems across domains: a Scala/Java media data warehouse with a custom query language and Elasticsearch search, plus production security patterns (RBAC, RLS, audit trails) including a telehealth platform. Also demonstrated strong operational rigor by using feature-flagged side-by-side migrations and by catching ecommerce checkout edge cases that were dropping revenue.”

“Frontend engineer with experience building a large-scale React + TypeScript administrative dashboard for an e-commerce platform, using Redux Toolkit plus TanStack Query to separate UI and server state. Emphasizes quality at scale through CI/CD automation, Jest/integration testing, and performance techniques like code splitting and caching, with experience coordinating integration across multiple teams.”

“Built a production GPT-4/LangChain/Pinecone RAG “AI Copilot” at Northern Trust to automate financial report generation and analyst Q&A over internal structured (SQL warehouse) and unstructured policy data. Focused on real-world production challenges—grounding and latency—achieving major speed gains (seconds to milliseconds) via MiniLM embedding optimization and Redis caching, and implemented rigorous testing/evaluation with MLflow-backed metrics while aligning compliance and finance stakeholders for deployment.”

“Cloud/hybrid infrastructure engineer with McKesson experience migrating tightly coupled healthcare applications to microservices on AWS EKS. Strong in IaC-driven standardization, CI/CD automation, and production observability (CloudWatch/Splunk/Prometheus/tracing), with demonstrated ability to debug complex incidents spanning Kubernetes and cloud networking.”

“Backend engineer who has shipped both high-throughput real-time systems and production LLM/RAG features. Built a database-free, local-first messaging service (Node/Express/Socket.IO) achieving ~1,500 msgs/sec at <25ms p95, and implemented a Go-based RAG recommendation pipeline with strict JSON/schema validation, catalog grounding, fallbacks, and eval loops that cut hallucinations to ~1–2% while reducing LLM costs ~60%.”

“Backend/platform engineer who built real-time connected-vehicle telemetry analytics at Subaru, spanning Kafka streaming, Python/FastAPI ETL, and low-latency WebSocket delivery (minutes to <2s). Strong Kubernetes + GitOps practitioner across AWS EKS and Azure AKS (Helm, ArgoCD, Jenkins/GitLab) and has led major on-prem-to-cloud migrations for financial microservices using Terraform and AWS DMS with measurable cost and reliability gains.”

“Front-end engineer with experience at Optum and Wells Fargo maintaining internal React/Angular component libraries and design-system-aligned UI modules used across multiple apps. Known for stabilizing shared libraries via semantic versioning, Jest test automation, and high-quality documentation, plus measurable performance wins (≈40% faster dashboard loads) through profiling-driven React and API optimizations.”

“JavaScript full-stack engineer with experience at EY building secure, cloud-ready React/Node.js applications on AWS and currently at startup Juego Juegos owning the AWS backend and CI/CD via AWS Amplify. Demonstrated impact through performance tuning of a React analytics dashboard (reduced initial load time ~20%) and resolving real payment failures by debugging Stripe 3DS flows and updating AWS Lambda plus frontend error handling.”

“Backend/AI engineer with production experience in payments/reporting systems and high-scale Node/NestJS services on AWS (ECS/ALB) using PostgreSQL, Redis, Kafka, Prisma, and Datadog. Shipped applied AI features including a Zendesk-embedded support copilot (summarization, draft replies, internal doc retrieval, playbook next steps) and an LLM-driven ops workflow agent with robust error taxonomy, retries/escalation rules, and auditability.”

“LLM/RAG practitioner building clinician-facing AI search and Q&A inside EHR workflows, focused on trust, latency, and safety (grounded answers with citations, PHI controls, encryption/audit logs). Demonstrated real-time incident response for production LLM systems (e.g., fixing a metadata-filter deployment regression to prevent irrelevant results/cross-patient leakage) and strong demo/enablement skills for mixed technical and clinical stakeholders; also shipped a multi-model RAG tool at OrbeX Labs with upload/search/audit features for day-to-day adoption.”

“Software engineer who built and open-sourced reusable React/Node.js modules (chat, auth, caching) from an AI education platform, emphasizing intuitive APIs and strong documentation. At TCS, improved a healthcare scheduling platform by diagnosing SQL/server bottlenecks and redesigning database + caching, cutting appointment load times by ~40% and reducing support complaints.”

“Founding engineer who built a multi-tenant AWS backend from scratch focused on ultra-fast, configuration-driven client onboarding and low operational cost. Automated tenant provisioning/deployments with Terraform + GitHub Actions (new client infra in ~13 minutes) and scaled to 62 production clients handling ~75k requests/day without a major rewrite. Hands-on with migrations (DynamoDB->MongoDB), reliability/observability, and performance tuning (indexes, Redis, queueing, connection management).”

“Backend engineer with experience at DigitalOcean and BNY Mellon, specializing in secure, highly available authentication and API platforms. Built an enterprise SSO system integrating Okta via OIDC with resilience patterns (gRPC contracts, circuit breakers, Kafka) and strong encryption, and led a careful monolith-to-Golang microservices migration using shadow traffic, dual writes, and feature flags to preserve data integrity.”

“Backend-focused Python engineer who builds modular Flask services on AWS and specializes in performance/scalability work across data-heavy APIs. Has concrete wins in query optimization (1.5s to <200ms) and high-throughput async processing (Celery+Redis, ~40% throughput gain), plus experience serving scikit-learn text classification models via containerized REST services and designing multi-tenant data isolation strategies.”

“Early-career cloud/appsec-focused engineer with hands-on experience building secure, observable microservice systems on AWS (IAM least privilege, KMS encryption, Secrets Manager, CloudWatch, ALB) and troubleshooting autoscaling-related 500s down to connection pooling issues. Also deployed heavy ML workloads on Kubernetes by decomposing diffusion/transformer services, using workload identity to eliminate static credentials, and maintaining GitOps-style deployment audit trails.”