Vetted Engineering Professionals

“Built and shipped a production LLM pipeline for nursing home Medicare reimbursement (PDF OCR + fact extraction + keyword RAG + QA) that reportedly increased payouts by ~$1K/month per patient. Strong in LLM ops/benchmarking (ground truth, LLM-as-judge, cost/I-O tracking) and pragmatic optimization—swapped retrieval approaches, fine-tuned a small model to cut OCR cost 90%, and migrated workloads to Azure/Temporal to scale nightly processing 10x.”

“Backend engineer with experience at Meta and Accenture building regulated-data systems (healthcare/financial) using Python/Flask and Postgres. Has scaled high-throughput services to millions of daily requests, delivering measurable latency wins (~40% API latency reduction; ~35% faster DB-backed endpoints), and has productionized ML inference services using Docker/Kubernetes and AWS (ECS/SageMaker).”

“Robotics software engineer with Amazon Robotics internship experience who built a visual-servoing architecture from scratch, navigating multiple simulator pivots to achieve a closed-loop motion-planning and execution prototype. Currently working with ROS 2 on a medical assistive feeding robot using the Kinova Kortex platform (MoveIt2, ros2_control, Gazebo/RViz), and has demonstrated strong real-time debugging and distributed-system synchronization using Carbon and Docker.”

“Backend owner at Apple for an AI workflow orchestration service, with hands-on experience stabilizing peak-traffic production systems using OpenTelemetry-style tracing, bounded async concurrency, and database performance tuning. Built and shipped a Python LLM-agent orchestration layer to automate multi-step operational workflows, emphasizing guardrails, auditability, and deterministic fallbacks to keep non-deterministic AI behavior production-safe.”

“Gameplay engineer with hands-on ownership of a real-time C++ combat ability system, including diagnosing and eliminating large-scale combat frame spikes by refactoring hit detection to an event-driven, animation-notify approach (cut collision checks ~80%). Also implemented UE5 networked abilities (dash) with client-side prediction and server-authoritative reconciliation, plus projectile ballistics validated through debug spline visualizations and unit tests.”

“Data/ML engineer who has owned end-to-end systems across email deliverability/segmentation and production LLM apps. Built a Spark+Airflow segmentation engine that materially improved deliverability (99.9%) and open rates (>50%), and shipped a PDF-to-quiz RAG product using LangChain/Vertex AI/Chroma with strong guardrails and an eval loop that cut hallucinations to <5%.”

“Full-stack engineer with experience across Magna, C3.ai, and Amazon, building GenAI-enabled products and finance transaction systems. Has shipped Next.js (App Router) + TypeScript features backed by Go/Python RAG pipelines, and emphasizes production quality via load testing, Selenium regression coverage, LLM-aware integration testing, and Azure observability. Also built LangGraph-orchestrated multi-step content generation workflows with robust retry/idempotency strategies.”

“Meta engineer focused on reliability/operations tooling who built a unified real-time health dashboard and scalable telemetry pipelines (AWS + Datadog) for thousands of devices. Also shipped an internal LLM-powered knowledge assistant using RAG over wikis/runbooks/logs with strong guardrails and a rigorous eval loop that drove measurable accuracy improvements via automated doc ingestion and embedding updates.”

“Platform and distributed-systems leader (player-coach) who owned architecture and reliability for an Amazon analytics/data platform serving ~100K internal users at exabyte scale. Built an ML-driven “Lakeflow” optimization layer that cut pipeline completion times ~20–25% and reduced compute waste >15%, and led major incident response/redesign efforts (e.g., deletion storm) with strong rollout/observability/rollback practices.”

“Series C (Sigma Computing) full-stack engineer/intern who shipped production features across React/TypeScript and GraphQL, including a Recents/workbook activity reliability improvement that handled unsaved “exploration” events via deterministic backend updates. Emphasizes production quality through Jest/Cypress coverage and feature-flagged staged rollouts, and is recognized for UX-focused improvements (fast, accurate filtering at scale) and proactive cross-functional ownership.”

“Robotics software engineer who delivered the Lunar ROADSTER—an autonomous bulldozing rover for lunar terrain manipulation—building the control system, path planning, and perception in ROS 2. Implemented crater detection using a YOLO model fused with ZED stereo depth to recover crater geometry, and structured autonomy around ROS 2 actions integrated into an FSM with CI/CD-backed system testing. Also has industrial robotics experience controlling a Fanuc arm for additive manufacturing and building ROS interfaces for PLC I/O.”

“Software Developer at Amazon Robotics who co-developed a congestion-aware path planning system optimizing robot routes across 23 warehouses. Built and operated a real-time, service-integrated pipeline using AWS (AppConfig, DynamoDB), Java, and Redis caching, and has hands-on experience debugging robot behavior on-site with rigorous testing and staged releases.”

“Customer Success Services / Support professional working on Palantir Foundry who productionizes customer integrations (secure OAuth2, scheduled pipelines) and builds LLM-driven support automation (runbook matching) with monitoring and evaluation suites. Also leads developer workshops/demos on Foundry packaging/installation workflows, using live debugging techniques to make concepts concrete.”

“Robotics controls engineer with experience spanning an RV/trailer automatic hitching and towing robot (vision + EKF sensor fusion, anti-jackknife/anti-sway, multi-loop torque assistance control) and 3 years on a ROS-based RoboTaxi autonomous driving stack at Pegasus Technology. Improved MPC trajectory generation robustness by converting hard constraints to soft constraints with slack variables, and built an AI-powered PR review agent (Claude-code) integrated into CI/CD to reduce bugs.”

“Product/UX designer who builds end-to-end systems across both consumer wellness and industrial/technical domains. Designed BloomPath (mental-wellness platform for therapists and young professionals) using research-driven, emotionally safe interaction patterns, and also simplified a Bosch autonomous parking vision-language mapping pipeline into a developer-facing real-time UI with layered debug tooling. Comfortable collaborating deeply with engineers and contributing in React/JS.”

“Product/UX designer with a CS/software engineering background at Microsoft (former intern, now full-time) who bridges design and implementation. Built Shiproom (a Twitch-like live-coding platform) end-to-end with a custom Atomic Design-based system, and has shipped impactful CRM improvements in Dynamics 365 for 60k+ support agents using TypeScript and C#. Also worked on a Microsoft Global Hackathon project integrating a Copilot-backed sign language translation model to reduce documentation friction for deaf support engineers.”

“Spatial computing software engineer focused on making Apple Vision Pro/visionOS accessible, including building VoiceOver and Live Captions features. Debugged a complex Live Captions issue involving dual audio inputs during FaceTime screen sharing by leveraging iOS implementation docs and creating concurrent audio sources; also has safety-critical testing experience from train control systems and is interested in pivoting into robotics.”

“Internship experience deploying cloud-based services into production, including navigating security/resource provisioning and coordinating approvals across impacted teams. Built a Python backend for a local Ollama-based app using open-source models, and has hands-on distributed systems experience implementing and debugging Paxos with extensive logging/state tracing.”

“AWS engineer who productionized an internal ML-driven data pipeline from a notebook prototype into a scalable, observable Python service (schema validation, deduplication, idempotency, safe retries, versioned transforms, CloudWatch alarms), reducing manual effort and improving data accuracy/trust. Experienced diagnosing workflow issues in real time (e.g., upstream schema changes) and partnering with account managers/support to unblock adoption of seller-facing Marketplace features by demonstrating reliability with concrete metrics.”

“Backend/platform engineer with hands-on ownership of Python services (Postgres/Redis/Celery) and measurable performance gains (~20–25%). Strong Kubernetes + ArgoCD GitOps experience delivering zero-downtime rollouts, plus led key reliability fixes (readiness probes, immutable tagging) and supported an on-prem to AWS migration using CDC replication and ALB traffic shifting; also built Kafka real-time analytics pipelines with schema registry.”

“Backend engineer with healthcare platform experience at Thirty Madison, combining Django for secure, data-heavy core services with FastAPI async microservices for real-time patient monitoring. Led Kubernetes migration with Istio service mesh, autoscaling (HPA), and stateful storage patterns, and implemented GitOps CI/CD using ArgoCD. Also built real-time Kafka streaming pipelines with reliability patterns like idempotent producers and offset management.”

“Built a production RAG-based natural-language-to-SQL system at Global Atlantic to replace slow, expensive manual analytics ticket workflows, focusing heavily on retrieval quality and measurable evaluation (200-question ground-truth set; recall@5 improved 0.65→0.78 via semantic chunking). Also built a custom MCP-style agent orchestrator for a personal project (arxiv-ai) to improve flexibility and Langfuse-aligned observability, and has hands-on experience with LangGraph, CrewAI, and n8n.”

“Built a production LLM-driven archival assistant that turns large, low-quality scanned handwritten files (120+ pages) into structured datasets, overcoming context-window and hierarchy challenges with a two-phase LLM + rules pipeline and reaching 98.1% accuracy (Gemini-2.5 Flash). Also orchestrated a large human-in-the-loop effort with 78 archivists, producing 2,400 high-quality annotations in 4 days via detailed rubrics and support.”