Vetted GitHub Professionals

“Robotics software engineer (PhD background) who owned an end-to-end autonomy stack for a 2025 GTC demo, integrating ROS2/MoveIt2 with a high-fidelity NVIDIA Isaac Sim environment for regression testing and sim-to-real validation. Has hands-on experience optimizing MoveIt2 planning (parallel pipelines + evaluation metrics) and building outdoor Nav2 localization using dual EKF with GNSS and LiDAR/IMU sensor fusion; currently building simulation environments at Richtech Robotics.”

“ML/AI practitioner in healthcare (Syneos Health) who has deployed production clinical NLP and risk models. Built a BERT-based physician-note information extraction system on Docker + AWS SageMaker (reported ~42% retrieval improvement) and automated retraining/deployment with Airflow and drift detection, while partnering closely with clinicians to drive adoption (reported ~18% readmission reduction).”

“Built and deployed a GPT-4-powered medical assistant for clinical staff to reduce time spent searching guidelines and EHR information, with a strong emphasis on safety and compliance. Uses strict RAG, confidence thresholds, and fallback behaviors to prevent hallucinations, and runs production-grade workflows orchestrated with LangChain/LangGraph plus Docker/Kubernetes/MLflow and monitoring for reliability and cost.”

“Solo developer who shipped an Android game (Master Caster) built around touch gesture recognition (P$ algorithm) and data-driven potion/ingredient systems using JSON/dictionaries. Has hands-on experience optimizing Unity projects for mobile constraints (framerate, heat/battery) using techniques directly applicable to VR, and is actively porting the game to VR in Unreal with a focus on accessibility and room/standing/seated play modes.”

“Frontend engineer on Ford EV infotainment HMIs building React + TypeScript workflows for Apple CarPlay/Android Auto device projection and high-stakes reset flows. Deep experience integrating a React HMI with legacy Qt expectations and C++ services via MQTT, using Redux Saga/state-machine patterns to manage complex async device and system operations with strong QA and performance optimization practices.”

“Full-stack engineer/product owner who built and scaled a customer-facing job application portal (Skillbridge) using TypeScript/React and Spring Boot/MongoDB, optimizing search performance with indexing, caching (Redis), and payload/lazy-loading improvements. Also built an internal AI-driven analytics dashboard for Salesforce operations using OpenAI sentiment analysis, achieving 70% reduction in manual analysis and driving adoption through demos and iterative feedback.”

“Full-stack engineer who built and owned an internal analytics dashboard for sales (React/TypeScript + Node/Express + NoSQL), delivering it two weeks early with zero production issues and a reported 10% sales-efficiency lift. Experienced with microservices and async messaging patterns (retries/DLQs/idempotency), and emphasizes rapid iteration with strong CI/CD and automated testing plus user-driven adoption.”

“Cloud-native integration engineer (Oracle/OCI) with strong production deployment and incident-response experience, including API gateway rollouts, observability (Prometheus/Grafana), and multi-layer debugging for payments systems. Built Python/FastAPI microservices and automation for customer-specific reporting and data sync, and has delivered major performance gains (45 min to <10) plus reliability improvements (MTTD reduced 40%+) through monitoring, playbooks, and resilient integration patterns (streaming/queuing, retries, secure tokens, VPC peering).”

“Software engineer with experience spanning an SEL internship and Walmart, combining backend/data pipeline work (Python, Kafka, relational DBs) with DevOps practices (Docker, Grafana, GitHub/Jenkins CI/CD, GitOps). Notably contributed to a REST-to-GraphQL migration aimed at reducing cloud utilization and implemented testing strategies to validate the transition.”

“Built and shipped multiple production LLM/agentic systems, including an agentic RAG NL-to-SQL analytics app that cut manual reporting from 9 hours/week to 15 minutes by grounding on schema-aware retrieval and robust fallback/monitoring. Also implemented a LangChain supervisor-orchestrated enterprise IT automation agent that routes requests for search, identity validation, and action execution, and created a RAG search tool spanning Jira/Confluence/SharePoint for operations stakeholders.”

“Backend engineer with Walmart experience owning Python data-processing/integration services alongside ASP.NET Core. Has deployed containerized services to Kubernetes via OpenShift with Jenkins CI/CD and GitOps-style config management, and has led phased migrations modernizing VB6/classic ASP apps to ASP.NET Core on OpenShift/Azure. Also implemented Kafka-based real-time pipelines with a focus on reliability, idempotency, and observability.”

“Backend/platform engineer (American Express) who built a Flask-based orchestration layer to automate infrastructure provisioning and integrated Azure AD/JWT RBAC security. Strong in PostgreSQL/SQLAlchemy performance optimization (70%+ query-time reduction) and scalable async/event-driven architectures, including ML inference pipelines (SageMaker/Azure ML/Hugging Face) and high-throughput job queues (Celery/Redis) with reliability patterns like DLQs and idempotency.”

“Healthcare-focused applied ML/LLM engineer who has deployed production systems including an LLM medical documentation assistant that summarizes unstructured EHR notes into physician-ready structured outputs. Experienced building secure, compliant pipelines (PHI minimization, RBAC, encryption) and scaling via Docker/Kubernetes/Azure ML, plus orchestrating ETL/ML workflows with Airflow and Kubeflow; also built an LLM-driven clinical coding assistant at Centene with measurable performance metrics.”

“Backend engineer at Cerebrone.ai building cloud-native Flask microservices for an AI-driven automation platform on GCP (Cloud Run/App Engine), including dedicated inference services integrating OpenAI and internal ML pipelines. Demonstrated strong performance and scalability wins across Postgres/SQLAlchemy optimization, multi-tenant (healthcare/HIPAA-grade) data isolation, and high-throughput background processing with Celery/Redis/RabbitMQ, with multiple quantified latency/CPU/throughput improvements.”

“Robotics-focused engineer from a senior capstone who built the backend motion-control software for a semi-autonomous line-following vehicle split across two ESP32s. Experienced in ROS 2 (DDS, lifecycle nodes, QoS) and in bridging microcontroller telemetry to a laptop ROS 2 stack over UART with custom structured protocols, using Gazebo simulation to tune PID and validate behavior before deploying to hardware.”

“Built and deployed a production LLM-powered text extraction/classification system that converts messy unstructured reports into searchable insights, running on AWS SageMaker with automated retraining and monitoring. Strong in orchestration (Step Functions/Kubernetes/Airflow patterns) and reliability practices (gold datasets, prompt/tool unit tests, shadow/canary/A-B testing, guardrails/rollback), and has experience translating non-technical stakeholder needs into an NLP workflow plus dashboard.”

“Co-founded a healthcare AI startup building and deploying software directly with end users, emphasizing rapid shipping, deep user interviews, and workflow-first adoption. Has hands-on production deployment experience on AWS (including diagnosing a silent AWS App Runner failure caused by an ARM vs amd64 Docker build mismatch) and is motivated by customer-facing, travel-heavy roles to keep engineering tightly connected to real-world usage.”

“Data/NLP practitioner with experience in both financial services (Truist) and government (USDA), including an NLP-driven analysis of EU regulations to anticipate US regulatory focus and a major redesign/cleaning of complex pathogen lab-test public datasets. Built production data-quality pipelines with Dagster, Pandera, and Azure Synapse, and is comfortable validating hypotheses with historical backtesting and SME-driven quality controls.”

“Customer-support/engineering background spanning Informatica PowerCenter ETL and IBM demos/workshops, with hands-on experience hardening data workflows for production (error tables/reject links, validation, restart strategies, alerting, performance tuning). Also demonstrates a clear, systems-level approach to diagnosing LLM/agentic workflow issues (prompt/RAG/tooling/memory) using instrumentation and iterative fixes, and has partnered with sales on POCs by defining success metrics and mapping solutions to customer architectures.”

“Backend engineer on Morgan Stanley’s trade risk and compliance platform, building Java/Spring Boot microservices that validate equity and fixed-income trades at multi-million-events/day scale. Shipped an LLM-assisted trade exception analysis feature using RAG over internal policy documents and trade history, with production-grade guardrails (confidence thresholds, audit logs, human-in-the-loop) and measurable performance wins (~30–35% faster reporting) through PostgreSQL tuning and Redis caching.”

“Backend-leaning full-stack engineer with production experience in both healthcare (claims enrichment/interoperability at Abacus) and finance (Goldman Sachs pricing/risk APIs + React dashboards). Built an event-driven AI grading platform using Postgres Debezium CDC + Kafka + FastAPI on AWS that cut manual grading ~70% and served 1000+ students, with strong emphasis on reliability, testing, and performance tuning.”

“Founder of an LLC operating as a consulting firm providing fractional CTO services to startups, giving them parallel exposure to multiple early-stage companies. Has direct experience with MVP development, building org structures from scratch, and supporting early fundraising, and is exploring a pivot from consulting into a scalable product business while staying engaged with the VC/accelerator ecosystem.”

“Azure cloud platform engineer with strong enterprise Linux operations background who designs multi-region HA/DR on Azure (and AWS) using Azure Site Recovery, Traffic Manager, AKS autoscaling, and geo-replicated Azure SQL. Built secure Azure DevOps CI/CD pipelines for .NET/Python microservices to AKS/VMs and provisions full environments via Terraform modules with remote state, drift checks, and staged rollouts; has not directly owned IBM Power/AIX at scale.”

“Currently at Huntington Bank, built a production-grade RAG system that helps business/operations teams get grounded answers from large volumes of internal enterprise documents. Owns ingestion and FastAPI backend, tuned hybrid BM25+vector retrieval and chunking for relevance, and evaluates reliability with metrics and observability (LangSmith, CloudWatch, Prometheus/Grafana) while partnering closely with non-technical stakeholders.”