Vetted Distributed Systems Professionals

“Amazon Fire TV Devices engineer who built and shipped a production LLM-powered lab triage and validation system that grounds recommendations in internal runbooks/known-issue data and pushes evidence-based actions via dashboards and Slack. Emphasizes safety and measurability with structured JSON outputs, replay-based evaluation on historical incidents, and production metrics (e.g., disagreement rate and time-to-first-action), plus cost/latency optimizations like caching, batching, and rule-based fast paths.”

“Engineering leader who drove TiVo IPTV’s client-facing API modernization from a monolith to AWS-based microservices (API Gateway, Lambda, EKS, Kafka, DynamoDB/RDS), including phased/blue-green production routing of millions of calls. Emphasizes org scaling through skill-based hiring, mentorship, and a you-build-you-run ownership culture, while balancing technical leadership with executive stakeholder communication and budgeting.”

“React-focused engineer who built a full-stack analytics/test-metrics dashboard (React frontend + Python backend) and turned common UI pieces (data tables, filter panels, chart wrappers) into a reusable internal component library with docs, examples, and basic tests. Strong on profiling-driven performance optimization (React Profiler, memoization) and on owning ambiguous internal-tool projects end-to-end; now planning to package internal patterns into public open-source components.”

“Backend engineer with SAP experience modernizing a legacy Flask/PostgreSQL product master data platform into a modular, stateless, containerized service with Kafka-based background processing and improved observability. Also has hands-on academic/side-project experience operationalizing ML (NLP retrieval with TF-IDF/BERT via FastAPI and CV lane-edge detection inference APIs using PyTorch).”

“Engineering/technology leader with experience at GE, Owl Cyber Defense, and Team Cymru, focused on translating VOC and business strategy into iterative product/technology roadmaps. Led delivery of a Continuous Threat Exposure Management/asset discovery capability integrated with threat intel, reaching GA in ~2 quarters and generating ~$300K in pre-GA orders. Has scaled engineering organizations significantly (to ~100 FTE) and driven big-data security architectures using Kafka and ClickHouse with data-driven cost/performance tradeoffs.”

“Software engineer with experience at Google and the City and County of San Francisco building production AI systems, including a RAG-based internal support chatbot and ML-driven ticket priority tagging. Has scaled data/ML platforms with Airflow on GCP (1M+ records/day, 99.9% SLA) and deployed multi-component systems with Docker and Kubernetes (GKE), using modern LLM tooling (LangChain/CrewAI, Claude/OpenAI, Pinecone/ChromaDB, Bedrock/Ollama).”

“Engineering/technology leader with mission-critical experience at JPL NASA on the Mars Curiosity Rover, delivering an AI-driven navigation system designed for zero tolerance for mistakes and reportedly operating with no failures for 15+ years. Also led a monolith-to-microservices, cloud-native migration that improved scalability by 300% and cut deployments from days to hours, and is comfortable switching between executive fundraising/stakeholder communication and deep technical leadership.”

“Backend/AI engineer who built and scaled an internal AMD semiconductor manufacturing microservice platform (SMR), reworking a synchronous lot-request workflow into an event-driven RabbitMQ/Celery/FastAPI pipeline. Diagnosed and fixed peak-load reliability issues using deep observability and Kubernetes autoscaling, cutting notification latency back to sub-second and reducing duplicates via idempotency/DLQs. Also shipped an LLM-powered natural-language search with schema-constrained JSON outputs and guardrails, plus a plan-execute-verify Jira bug-resolution agent that can propose fixes and raise PRs under restricted permissions.”

“Backend/product engineer with Tesla experience building and operating a real-time OTA update monitoring and fleet analytics platform at massive scale (telemetry from 3M+ vehicles). Delivered end-to-end systems across Kafka-based ingestion, TimescaleDB/Postgres analytics modeling, FastAPI/GraphQL APIs, and React/TypeScript dashboards, and handled production scaling incidents on AWS EKS during major rollout spikes.”

“Owned and built Bloomberg’s end-to-end bitemporal dividend & dividend-forecast data platform powering BQL for 400k+ terminal users. Architected real-time Kafka ingestion (5k–10k msgs/sec) across 100k+ tickers with strong correctness guarantees (PIT/bitemporal time-travel, immutable history to avoid look-ahead bias) and achieved sub-100ms p95 query latency through indexing and caching, deployed with Kubernetes + DLQ and robust monitoring.”

“Gameplay engineer with hands-on experience across Unreal Engine 5 and Unity, owning systems from level streaming/teleportation to motion-matched character movement. Has shipped/implemented multiplayer features including GAS-based replication with prediction/reconciliation and a deterministic lockstep runner using fixed-point math. Strong at diagnosing hard-to-repro physics issues and balancing performance/feel (e.g., mobile voxel A* pathfinding at 60 FPS, Chaos destruction tuned to avoid trapping players).”

“Robotics software engineer at Tesla who led end-to-end development of a distributed real-time control and orchestration platform for autonomous systems. Deep production ROS 2 experience (nav2, slam_toolbox), with demonstrated wins reducing end-to-end latency 25–30%+ via profiling, multithreaded executors, and QoS tuning, plus simulation and deployment at scale using Gazebo/Webots, Docker/Kubernetes, and CI/CD.”

“LLM engineer who has deployed privacy-preserving, real-time workplace risk monitoring over massive enterprise chat/email streams, tackling latency, hallucinations, and extreme class imbalance with model benchmarking, RAG + fine-tuning, and a pre-filter alerting layer. Also built an agentic legal contract drafting system (Jurisagent) using LangGraph/LangChain with deterministic multi-agent control flow, structured outputs, and reliability-focused evaluation/telemetry.”

“Built a production LLM-powered analyst assistant at Discern Security to speed up SOC investigations using a RAG pipeline over security vendor documentation (Python PDF ingestion, vector search). Demonstrates deep, security-critical LLM engineering: structure-aware chunking with custom table parsing, grounded/cited responses, prompt-injection defenses, and post-generation validation, validated via golden datasets and adversarial testing; tool is used daily by analysts.”

“Software engineer who owned customer-facing, high-traffic TypeScript/React + TypeScript backend systems end-to-end, emphasizing safe velocity through feature flags, staged rollouts, observability, and rollback-ready incremental delivery. Reports shipping more frequently with fewer production incidents and faster recovery due to these guardrails.”