Vetted Engineering Professionals

“Former Amazon intern who owned an end-to-end computer vision system to detect package anomalies in fulfillment centers, from data collection/labeling to production deployment on AWS (EC2/S3) with a Streamlit live-monitoring dashboard. Also has ML-in-production experience deploying and updating a recommendation model on Kubernetes (Minikube) with CI/CD via GitHub Actions, plus prior SDE experience with Jenkins-based pipelines and on-prem to AWS migration work using Glue.”

“Platform/backend engineer focused on Kubernetes at scale: built a Java control-plane service for multi-region cluster provisioning/monitoring/upgrades using Kafka-driven async workers, and solved peak-load provisioning failures by eliminating blocking I/O and dynamically scaling consumers. Also shipped an LLM-assisted Kubernetes troubleshooting/remediation feature that pulls Prometheus logs/metrics into prompts and uses guardrails (confidence thresholds + human-in-the-loop) to prevent risky actions.”

“Backend engineer with ad-tech experience who improved advertiser dashboard accuracy by exempting 1% of traffic from ML-based dropping in a ~1B-requests/day pipeline, trading storage for higher customer satisfaction and reduced debugging load. Demonstrates strong migration discipline (phased rollouts, compatibility layers, rollback/change-history recovery) and production API/security practices in Python/FastAPI (async, caching, throttling, RBAC/RLS, monitoring).”

“Backend engineer with Tesla experience who redesigned vehicle registration into a step-based, region-configured workflow across 4–5 microservices, enabling partial saves and reducing customer drop-off. Has hands-on experience scaling and securing Python/FastAPI APIs (OAuth2/JWT, CORS), migrating cold data from MySQL to MongoDB via Kubernetes CronJobs, and implementing RBAC/RLS with Supabase + Postgres.”

“Meta engineer who improved a critical revenue estimation dataset pipeline that was arriving ~6 days late—diagnosed via raw logs/lineage, redesigned legacy scans to only process the needed window, and shipped validation plus freshness/lag dashboards. Delivered ~50% latency reduction (to ~3 days) and regained adoption by running old/new pipelines in parallel with gated cutover and evidence-based customer communication. Applies incident-response rigor to real-time LLM/agentic workflow debugging and regularly runs developer demos/workshops.”

“Backend engineer who scaled a food delivery platform by migrating from a single-service architecture to Spring Cloud microservices with an API gateway and Kafka-based event-driven order pipeline. Reported outcomes include ~50% latency reduction, stable ~2K RPS throughput, and 99.8% uptime, with strong emphasis on safe migrations (dual writes, canaries, schema versioning) and security (JWT/RBAC/Postgres RLS).”

“QA professional with experience at Google and Meta, focused on end-to-end functional/regression testing, disciplined bug reporting (including ADB logs), and release readiness via staging build promotion and gating on critical/high-priority issues. Emphasizes PRD-driven test planning, edge-case coverage (e.g., low connectivity/low battery), and thorough verification across build versions.”

“Aspiring founder exploring an AI automation startup focused on automating processes involved in building companies. Not yet developed specific use cases or raised capital, but describes a clear plan to validate ideas through use-case research, building a pilot, and testing with early customers; not familiar with the VC/accelerator landscape yet.”

“Entrepreneurially minded builder focused on proving architecture concepts via minimal demo prototypes for marketing. Has hands-on experience improving an A/B experimentation framework by interviewing stakeholders, identifying system limits and bottlenecks, and defining success criteria to scale experimentation and speed up analysis.”

“Backend/data engineer with Amazon supply-chain experience building production serverless Python services and ETL pipelines on AWS (Lambda, API Gateway, S3, RDS, Glue). Has modernized legacy SAS jobs into Python with rigorous parity testing and phased migrations, and has delivered major SQL performance gains (minutes down to seconds) through indexing and partitioning.”

“Backend/data engineer from Oscar Health specializing in healthcare claims systems on AWS. Built HIPAA-compliant real-time services (FastAPI/Postgres/Kafka on EKS) and serverless ingestion pipelines, and led modernization of a legacy SAS claims pricing system to Python/Spark with rigorous parity validation. Demonstrated measurable impact with high uptime/low latency services and major Snowflake performance and cost reductions.”

“Backend/data engineer with hands-on production experience across GCP (FastAPI microservices on Kubernetes) and AWS (Lambda, ECS Fargate, Glue). Has modernized legacy SAS batch systems into Python services with parallel-run parity validation, and has strong operational rigor in ETL reliability/monitoring plus proven SQL tuning impact (25s to <300ms, ~60% CPU reduction).”

“Backend/platform engineer with experience at Microsoft, Uber, and Gusto building production AI-agent automation systems in Python (AutoGen) and cloud-native microservices on Kubernetes across AWS/Azure. Has delivered zero-downtime migrations and high-throughput real-time streaming pipelines (Kafka/WebSockets/Redis), and is strong in GitOps/ArgoCD-driven CI/CD with reliable rollouts and rapid rollback.”

“DevOps/SRE focused on cloud-based distributed systems, with strong hands-on Kubernetes production experience (microservices deployments, Helm, probes, resource tuning, CI/CD and Docker build standardization). Demonstrated end-to-end troubleshooting across application, infrastructure, and networking layers—e.g., isolating degraded storage via node disk I/O metrics and restoring performance by draining the node and replacing the volume. Builds Python automation for operational reliability, including scheduled Kubernetes secrets rotation integrated with an external secret manager.”

“Gameplay engineer/designer with Unity experience spanning a Peloton open-world multiplayer cycling game (progression, difficulty normalization via FTP, replayability through medals/cosmetics) and a mixed reality soccer training game using a motion-tracked ball. Known for pragmatic, metrics-driven tuning (session length/mission duration), rapid playtest-led iteration, and cross-discipline execution including performance tooling (LOD batch editor) and phased multiplayer implementation planning.”

“Built an autonomous-agent document indexing concept in a hackathon with Microsoft and The Seattle Times, architecting an Azure-based system (Azure AI Foundry, Cosmos DB, Azure indexing, Copilot Studio) and coordinating closely with the customer team. Also created and pitched a sports matchmaking app (Ludicon), combining user studies, feature implementation, and technical support on sales/investor calls.”

“Robotics/embedded engineer with hands-on experience building real-time control systems on RP2040 (hydroponics automation, 1-DOF helicopter stabilization) and full ROS 2 navigation stacks in simulation (URDF, TF, PID, A* in RViz/Gazebo). Demonstrates strong low-level protocol work (timing-sensitive one-wire in C) and rigorous debugging across hardware and software using UART instrumentation and oscilloscope verification, plus reproducible workflows with Docker and CI/CD (GitHub Actions/GitLab, incl. Sandia National Labs).”

“Backend/data engineer with healthcare/telehealth domain experience, building patient appointment and data-processing systems on AWS. Has delivered production microservices and ETL pipelines (Flask/Celery, Glue/PySpark) with strong reliability/observability practices (JWT, retries/timeouts, Sentry/CloudWatch) and modernization experience migrating SAS workflows to Python services, including a documented 10min→30sec SQL performance win.”

“Frontend/UI lead who drove an end-to-end Angular redesign at Ketto.org, creating a scalable design system and internal component library with 90%+ unit test coverage and ongoing performance work (FCP/TTI, SSR/CDN/caching). More recently at Google, built a complex React+TypeScript UX research platform syncing video playback with interactive transcripts (notes/tags/highlights) and shipped features via PRD-driven, phased rollouts with dogfooding and in-app feedback.”

“Amazon Robotics engineer who deployed and scaled the Lumos camera-based package scanning work cell across EU sort centers (100+ work cells in 5+ sites), enabling remote launches via detailed runbooks and troubleshooting. Strong in AWS IoT/edge systems, with hands-on incident recovery (restored 34 down work cells) and secure multi-compute certificate provisioning using IoT Jobs, ACM/CA, and custom roles; delivered ~75% per-cell cost reduction vs Cognex-based approach.”

“JavaScript/TypeScript engineer from Ridgeline who built a retry feature for failed staging-to-production promotions with pre-promotion health checks. Brings a backend-scaling mindset to runtime performance work (metrics-first bottlenecking, Big-O analysis, async/parallelism, caching) and leverages Cursor/AI tooling to ramp quickly on large codebases.”

“Robotics engineer who helped bootstrap Meta’s humanoid robotics effort, building simulation training and deployment infrastructure for vision-language-action (VLA) models. Evaluated multiple physics backends (Bullet, MuJoCo, Isaac, internal) to minimize sim-to-real gap and addressed control-loop frequency mismatches via sequence optimization/MPC-like approaches and trajectory-output modifications. Published research that contributed a new addition to ROS 2 and has built ROS2 node stacks spanning control, perception, teleop, tactile sensing, and imaging.”

“AWS engineering manager leading delivery for an end-to-end encrypted communications product (calling/messaging/screen sharing), including shipping read receipts with full design/engineering/QA ownership. Demonstrated strong customer-driven problem solving (offline/mission users enrollment via admin one-time codes with account allowlisting) and reliability improvements (data retention bot crash RCA, monitoring/notification, and high-volume test simulation).”

“Backend/AI engineer who built a production GPU-backed real-time inference API at Nvidia and debugged burst-induced tail latency, cutting P95 by ~29% through dynamic batching and backpressure. Also shipped an end-to-end RAG + agentic operational diagnostics assistant with strict tool controls, evidence citation, confidence gating, and strong production guardrails, plus demonstrated hands-on Postgres optimization (900ms to 40–60ms).”