Vetted Engineering Professionals

“Frontend engineer who led Bentley’s flagship design system from a greenfield codebase to adoption across every major Bentley product, emphasizing maintainability and high UX polish. Built complex React+TypeScript interfaces like a Figma/Photoshop-style layers tree, applying advanced performance techniques (skeleton-first loading, transitions, memoization, deferred rendering) and iterative feature-flagged rollouts driven by user feedback.”

“Hands-on engineer focused on productionizing LLM-powered assistants: builds RAG pipelines with guardrails, response schemas, and citation-grounded outputs, then hardens them with explicit NFRs (latency, uptime, security, cost). Experienced diagnosing agentic/LLM workflow issues in real time using observability and stepwise isolation, and supports go-to-market via developer demos, workshops, and pre-sales technical evaluations in microservices/Spring Boot environments.”

“Backend-leaning full-stack engineer who has built and operated event-driven microservices platforms (FastAPI/React/TypeScript, Kafka, Kubernetes) and internal DevOps tooling. Delivered measurable impact through user-feedback-driven iteration (WebSockets update mechanism cutting redundant API calls ~30%) and operational improvements (deployment monitoring dashboard reducing rollback time ~40%), with strong focus on reliability, observability, and data consistency at scale.”

“Software engineer and University of Chicago graduate teaching assistant who built a full-stack internal analytics dashboard (React/TypeScript + Node/Express) and worked in RabbitMQ-based microservices with Prometheus/Grafana observability. Also created an AI-powered ERD diagram generator (React + MermaidJS + OpenAI) adopted by students to save hours on database assignments, using validation loops to ensure valid Mermaid output.”

“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.”

“Full-stack engineer who has owned React/TypeScript + Spring Boot dashboard products end-to-end, including real-time performance/alerts and data aggregation across services. Strong in shipping MVPs quickly with feature flags, automated testing and CI/CD, and using monitoring/click-path analytics to prioritize work—achieved a 40% page-load reduction. Experienced operating microservices with RabbitMQ at scale, addressing retries/idempotency/observability and fixing duplicate-processing incidents with idempotent consumer patterns and DLQs.”

“Backend engineer who built an AI RAG quoting system for the fastener industry, reducing quote turnaround from weeks to ~30 minutes and raising retrieval accuracy to ~90% by solving a semantic-collision issue with a parent-document retrieval design. Strong in production AWS integrations (Cognito auth, S3 pre-signed uploads), performance optimization (multithreading/out-of-core), and real-time streaming (Kafka/Spark Kappa architecture achieving sub-second latency), plus Kubernetes logging and GitHub Actions CI/CD to ECR.”

“Python backend engineer who owned an end-to-end Django/DRF authentication and account-management module (JWT, RBAC, email verification) and optimized token validation performance. Has hands-on Kubernetes + Helm delivery with GitOps via ArgoCD (multi-environment app-of-apps, drift detection/rollback) and has supported a cloud-to-on-prem migration using staged testing and phased cutover. Also built and scaled a Kafka-based real-time user activity tracking pipeline with reliability and backpressure controls.”

“Post-graduate, self-directed robotics/RL practitioner who independently built a modular reinforcement learning training framework in Python using Stable-Baselines3, Gymnasium, and PyTorch. Emphasizes reproducible experimentation (multi-seed validation), simulation (PyBullet/Box2D), and systematic comparison of algorithms/environments via a factory-pattern architecture.”

“Engineering leader with a strong automation-first philosophy ("special treatment doesn't scale"), experienced in building self-service tooling and communicating clearly with executives via BLUF-style updates. Has delivered end-to-end business-driven solutions—from sourcing alternative vendor data to installing infrastructure and writing drivers/analytics—and led pragmatic architecture changes in R/Rserve that significantly improved performance while driving cloud costs toward near-zero.”

“Robotics software engineer who built and deployed a full custom ROS navigation stack (global/local planners) for a TurtleBot3 reconnaissance robot, validated in Gazebo and on real hardware. Has hands-on experience customizing MoveBase for an autonomous warehouse mobile robot internship and optimizing multi-robot ROS communications by pruning and throttling high-volume sensor streams, plus CI/CD automation via Bitbucket Pipelines and Docker.”

“Software engineer with healthcare domain experience (patient monitoring and provider systems) who improves reliability and performance in complex React/Flask applications. Led API standardization for shared internal React utilities using an RFC + deprecation strategy, and optimized a live WebSocket dashboard to handle 3000+ concurrent clinics while reducing client CPU usage. Strong in production debugging, data ingestion validation, and operational improvements like structured logging and alerting.”

“Mobile game QA tester (1 year on iOS/Android) eager to transition into console testing, with a strong grasp of console certification concepts (Sony TRC, Microsoft XR, Nintendo Lot Check) and a showstopper-first triage mindset. Experienced with TestRail/Zephyr, regression cycles, and leveraging AI for log analysis and report tagging to speed up QA workflows.”

“Full-stack engineer with Deloitte and CrowdDoing experience shipping production web platforms on AWS (EC2/RDS/S3/Fargate) using React/TypeScript and Node/Express/PostgreSQL. Built customer-facing authentication/SSO flows (OAuth2 + JWT) and state-specific US privacy consent workflows, and also delivered a Python/Flask LLM-based finance document parser chatbot with vector DB integration and latency optimizations.”

“Backend/infrastructure-focused engineer building AI-agent products for small businesses, including a customer-service agent platform with intent routing, RAG over Pinecone, and external booking API integration. Has shipped Python/FastAPI services with JWT auth, versioned APIs, Docker deployments to AWS EC2 via GitHub Actions, and production monitoring with Prometheus/Grafana.”

“AAA sports game QA tester who supported full development through launch and live updates, owning gameplay stability/regression risk. Experienced in triage-driven prioritization and in diagnosing complex crash issues (including thread synchronization) using evidence-backed Jira reports, then hardening coverage with stress/concurrency/soak and CI-integrated regression suites.”

“Cloud-native infrastructure and application security practitioner focused on AWS multi-account environments, partnering with engineering teams on threat modeling, secure architecture reviews, and secure SDLC alignment. Has implemented IaC-driven centralized logging/SIEM and improved IAM and logging redundancy to strengthen both security posture and operational resilience, plus maintained secure CI/CD pipelines with integrated security scanning and release guardrails.”

“QA professional with live production testing experience in an Agile pipeline, using risk-based coverage, smoke + automated regression (Postman), and strong defect/triage practices in JIRA. Emphasizes requirements traceability in TestRail and uses SQL/API/database evidence to isolate unclear repro issues and speed developer triage.”

“Backend engineer with airline operations domain experience who modernized flight-ops systems from batch updates to real-time streaming on AWS (Kafka + Spring Boot microservices), improving latency and stability through metric-driven tuning and idempotency. Also shipped a production LLM decision-support component using RAG over operational logs and internal procedures, with strong guardrails and an evaluation/regression loop to reduce hallucinations and enforce grounding.”

“Dedicated engineer supporting the T-Mobile enterprise account at Gigamon, leading annual large-scale device upgrade initiatives (2000+ devices in 1–2 months) with an emphasis on zero production traffic disruption and strong stakeholder communication. Known for consistently high CSAT (4.8+) and for driving operational improvements in Salesforce that cut support Time to Close by 50%.”

“QA engineer with 12 years of experience in SaaS/platform releases (not AAA games), partnering closely with developers and product through standups, 1:1s, and Three Amigos. Owned high-risk areas like payment data integrity and critical user journeys, running CI-based full regression to support go/no-go decisions. Notably caught a production EV charging receipt defect (zero charge shown) and drove it to resolution with strong Jira documentation and cross-functional escalation.”

“Unity VR developer who has shipped on Meta Quest, including Metro Awakening (Steam Awards 2024 VR Game of the Year) as an AI Programmer, focusing on performance-critical multi-agent AI optimization (EQS/HTN) for Quest 2. Also shipped Final Fury, taking ownership across gameplay, UI, networking (sync mechanics), and AI on a small team, and built a data-driven gesture/move system for VR fighting prototypes.”

“IBM Power/AIX infrastructure engineer who owned a very large production estate (12 Power9 E980 frames and 400+ AIX 7.2 LPARs) with deep hands-on expertise in VIOS/vHMC, DLPAR, and PowerHA. Demonstrated strong incident response (zero-downtime DLPAR fix; split-brain prevention during storage failure) and modernization skills spanning Jenkins/Ansible CI/CD and Terraform automation for IBM Power Virtual Server/PowerVC.”

“Built and shipped an AI-driven interview evaluation pipeline at SeekOut that automated recruiter screening via a multi-stage LLM agent workflow (.NET backend, RabbitMQ orchestration, Python workers). Emphasizes production-grade reliability (idempotency, retries, strict JSON/schema validation), strong observability with OpenTelemetry, and measurable efficiency gains including ~40% reduction in token usage/cost.”