Vetted Git Professionals

“Engineering leader and former CTO/Disney|ABC engineering manager who built white-label mobile app architecture that supported a branded app and successful exit, and later scaled Disney Channel brand app teams across iOS/Android/web and major OTT platforms. Led kid-safety architecture for DisneyNOW (“Junior mode” with PIN) and partnered with product/legal on COPPA compliance, emphasizing maintainable tech choices and strong execution processes.”

“Backend/ML platform engineer from Snapsheet who owned production Python services and data pipelines for insurance claims, including an AI document classification/summarization FastAPI service on ECS/Fargate processing 1M+ documents/year. Strong in AWS infrastructure (Terraform, CI/CD, secrets/IAM, autoscaling), Glue/PySpark ETL with schema evolution controls, and legacy SAS-to-microservices modernization with safe, feature-flagged rollouts and measurable performance wins.”

“Senior Engineering Manager with large-scale platform/API ownership at eBay, leading a globally distributed team and redesigning Order public APIs used by external developer ecosystems at ~800M requests/day, delivering 84% performance gains and reducing compute by ~300 VMs. Also led Google CRES ETL migration work on GCP, creating reusable Python libraries to standardize configuration across 10 integrations and improve developer productivity.”

“Robotics software engineer/research lead building an off-road mobile base, owning system integration across mechanical/electrical/embedded and developing controls + motion planning deployed from simulation to hardware with ROS 2/ROS 2 Control. Has deep ROS 2 experience (NAV2, MoveIt) and built a GridMap-based off-road elevation-to-traversability mapping stack using nonlinear optimization; also tuned real robots using Vicon and developed a quadcopter geometric/PID controller.”

“Backend/data engineer with experience at Nike building high-volume order orchestration and validation APIs using FastAPI microservices on AWS EKS with Kafka, Redis, and Postgres. Strong in production reliability (timeouts/retries/idempotency), GitOps (Argo CD) + Terraform deployments, and data pipelines (AWS Glue/S3), with hands-on incident ownership and legacy modernization into API-driven services.”

“Senior, product-focused engineer who has built real-time customer-facing web applications and a microservices backend (TypeScript/React/Node) using RabbitMQ, MongoDB, and Redis. Demonstrates strong operational maturity (idempotency, tracing/observability, backpressure) and built an internal console that became the primary tool for debugging, replaying jobs, and managing system behavior.”

“Engineering leader who built and delivered an IoT smart-spaces platform for the self-storage and smart-living domains, translating customer requirements into architecture, capability maps, and a multi-milestone roadmap. Personally stood up missing AI/ML capabilities (including churn prediction) using Databricks (Delta Lake/MLflow), enabling follow-on features like energy optimization and security/anomaly detection. Scaled an org from 20 to 80+ with disciplined Agile planning (Jira Advanced Roadmaps/Confluence) and strong executive/customer-facing leadership during high-stakes customer commitments.”

“LLMOps-focused technical leader who took an LLM use case from prototype to production for a non-technical customer by combining trust-building and structured enablement with a robust AWS/Kubernetes-based MLOps stack. Built observability and rollback mechanisms (Grafana + MLflow) to troubleshoot in real time, and scaled delivery by hiring a 5-person team while partnering with sales to manage expectations and drive adoption across departments.”

“Amazon engineer/leader who drove a major modernization of the AWS Database Migration Service Console, migrating a monolithic UI to a micro-frontend architecture while improving performance, reliability, and engineering standards. Operates as a player-coach (80/20 hands-on/management), with demonstrated incident ownership and process improvements across Amazon and Walmart Labs.”

“Robotics student who built a fully autonomous "Pacman" robot car using ROS 2, integrating LiDAR/IMU sensing with localization, autonomous driving, and a custom RRT + A* planner. Demonstrated practical embedded optimization on an RP2040 by balancing replanning frequency with safety via rapid collision checks.”

“AI/LLM engineer with production experience at NVIDIA and Microsoft, including building a RAG-based enterprise knowledge assistant that improved accuracy by 42% and scaled to thousands of queries. Deep in inference optimization (TensorRT-LLM, Triton, quantization, speculative decoding) and MLOps/observability (Prometheus/Grafana, MLflow, LangSmith), plus orchestration with Kubeflow/Airflow across multi-cloud.”

“Amazon internship experience building production GenAI analytics for the returns organization: a multi-agent LLM+RAG system that let analysts query multiple heterogeneous data sources in natural language without hand-written SQL. Also built and operationalized four Apache Airflow DAGs for large-scale ETL, emphasizing observability and freshness-aware metadata to keep outputs accurate and up to date.”

“Game UI engineer with shipped experience on Paladins (Unreal Engine 3/C++), including an in-game store with automated grid-based recommendation layout and an inventory UI built for PC/PlayStation/Xbox/Switch. Emphasizes production readiness through clean separation of UI/data, strong documentation for engineering and content workflows, and memory-conscious UI patterns (pooled entries/paged navigation) for constrained platforms like Switch.”