Vetted CI/CD Professionals

“Data engineer focused on large-scale financial data platforms, with hands-on ownership of an AWS + Databricks + Snowflake pipeline processing ~2TB/day. Strong in data quality (Great Expectations), schema drift automation, and production reliability (99.9%), plus measurable performance/cost wins (4h→1.2h, ~25% cost reduction). Also built an async Python crawling/ingestion framework with anti-bot mitigation, retries, and Airflow-driven backfills.”

“Senior full-stack engineer with strong healthcare domain experience who has shipped an Azure OpenAI RAG-based patient medication support chatbot to production, driving ~10K queries/month and a reported 38% reduction in call center volume. Also builds polished real-time React/TypeScript pharmacy tooling and operates large-scale Python/Spark ETL pipelines (~12M records/day) with strong API design, observability, and cloud deployment experience across Azure/Kubernetes and AWS.”

“Founding engineer who built a multi-tenant AWS backend from scratch focused on ultra-fast, configuration-driven client onboarding and low operational cost. Automated tenant provisioning/deployments with Terraform + GitHub Actions (new client infra in ~13 minutes) and scaled to 62 production clients handling ~75k requests/day without a major rewrite. Hands-on with migrations (DynamoDB->MongoDB), reliability/observability, and performance tuning (indexes, Redis, queueing, connection management).”

“Robotics software engineer with a Master’s thesis building an end-to-end monocular-vision pick-and-place controller for construction use cases on TurtleBot3 + OpenManipulator, spanning synthetic data creation, transfer learning, simulation in Gazebo, and real-robot deployment. Leveraged ROS distributed architecture to run two heavy AI models across networked GPUs to achieve usable real-time performance, and has production CI/CD experience as a Senior Software Engineer in AI/analytics.”

“Backend engineer with hands-on experience scaling a CVE processing platform by re-architecting it into a Kafka-based distributed system, boosting throughput to 200k+ records/min while designing for HA, deduplication, and fault tolerance. Also led a Flyway-driven migration affecting 15M+ records with staged dev→stage→prod rollout, and has implemented production security patterns (Auth0, OAuth2/HTTPS, AWS IAM RBAC) including least-privilege hardening.”

“Backend/data engineer with production experience building real-time sensor telemetry platforms: FastAPI + PostgreSQL services with strong observability, plus AWS serverless and Glue-based ETL into Redshift. Has modernized legacy SAS pipelines into Python microservices and delivered measurable performance wins (Postgres query latency cut to <1 minute and ~60% DB CPU reduction) while owning incident response and reliability improvements.”

“LLM/agentic systems builder who shipped production workflows at Angel Flight West and Eureka AI, combining LangGraph + RAG (Postgres/pgvector) with strong observability (LangSmith/Langfuse). Delivered large operational gains (address lookup cut from 10 minutes to 60 seconds; accuracy to 92%) and has a track record of quickly stabilizing customer-critical pipelines (Pydantic-enforced JSON for ETL) while partnering with sales/ops to drive adoption.”

“AI engineer at Cleveland Clinic building production LLM/NLP systems for radiology documentation, focused on HIPAA-aware, real-time performance across ~298 campuses. Re-architected infrastructure with AWS event-driven services to handle scaling and improved SLA compliance ~40%, and complements this with a personal multi-agent debate system (CrewAI) using local Llama/Mistral plus rigorous evaluation (A/B tests, red teaming, observability).”

“Unity/Meta Quest VR developer who helped ship a pharmaceutical lab-training simulator, owning key interaction systems (liquid transfer, pipette behavior) and building custom editor tooling to accelerate objective testing. Also built a solo early-lifeform simulation featuring procedural soft-body mesh generation and physics-driven animation, demonstrating strong systems/physics programming depth.”

“Frontend engineer who co-built an AI-enabled marketing automation platform with multi-workspace tenancy, implementing database-scoped queries and RLS for isolation plus real-time UX (chat, voice transcription via Deepgram, autosave, Supabase Realtime). Emphasizes quality and speed through CI practices (linting/unit tests, planned Playwright) and has shipped fast iterations like Stripe prepaid card detection from overnight build through staged QA to production.”

“AI/ML engineer with experience at Northern Trust and Persistent Systems building production LLM + RAG systems for regulated financial use cases, including liquidity forecasting, anomaly detection, and credit scoring. Emphasizes compliance-first design with explainability (SHAP), traceability (MLflow), and hallucination controls (FAISS + citation-grounded prompting), and has delivered drift-triggered retraining pipelines using Airflow and Kubernetes while translating model outputs into business-ready marketing segments.”

“Built and deployed a production LLM/RAG clinical document understanding and summarization system for healthcare, focused on reducing manual review time while meeting strict accuracy, latency, and compliance needs. Demonstrates strong MLOps/orchestration depth (Airflow, Kubernetes, Azure ML Pipelines) and a rigorous approach to hallucination mitigation through layered, source-grounded safeguards and stakeholder-driven requirements with physicians/compliance teams.”

“Frontend engineer focused on scalable React/Redux + TypeScript applications, with hands-on experience designing reusable component architectures, improving performance (reducing re-renders, streaming API calls), and hardening maintainability through standardized styling and unit tests. Has shipped deadline-driven dashboard features (e.g., filters) using Agile practices and Jira to manage QA and client feedback.”

“Frontend engineer who led Bentley’s flagship design system from a greenfield codebase to adoption across every major Bentley product, emphasizing maintainability and high UX polish. Built complex React+TypeScript interfaces like a Figma/Photoshop-style layers tree, applying advanced performance techniques (skeleton-first loading, transitions, memoization, deferred rendering) and iterative feature-flagged rollouts driven by user feedback.”

“Hands-on engineer focused on productionizing LLM-powered assistants: builds RAG pipelines with guardrails, response schemas, and citation-grounded outputs, then hardens them with explicit NFRs (latency, uptime, security, cost). Experienced diagnosing agentic/LLM workflow issues in real time using observability and stepwise isolation, and supports go-to-market via developer demos, workshops, and pre-sales technical evaluations in microservices/Spring Boot environments.”

“Backend-leaning full-stack engineer who has built and operated event-driven microservices platforms (FastAPI/React/TypeScript, Kafka, Kubernetes) and internal DevOps tooling. Delivered measurable impact through user-feedback-driven iteration (WebSockets update mechanism cutting redundant API calls ~30%) and operational improvements (deployment monitoring dashboard reducing rollback time ~40%), with strong focus on reliability, observability, and data consistency at scale.”

“Software engineer and University of Chicago graduate teaching assistant who built a full-stack internal analytics dashboard (React/TypeScript + Node/Express) and worked in RabbitMQ-based microservices with Prometheus/Grafana observability. Also created an AI-powered ERD diagram generator (React + MermaidJS + OpenAI) adopted by students to save hours on database assignments, using validation loops to ensure valid Mermaid output.”

“Backend-focused Python engineer who builds modular Flask services on AWS and specializes in performance/scalability work across data-heavy APIs. Has concrete wins in query optimization (1.5s to <200ms) and high-throughput async processing (Celery+Redis, ~40% throughput gain), plus experience serving scikit-learn text classification models via containerized REST services and designing multi-tenant data isolation strategies.”

“Full-stack engineer who has owned React/TypeScript + Spring Boot dashboard products end-to-end, including real-time performance/alerts and data aggregation across services. Strong in shipping MVPs quickly with feature flags, automated testing and CI/CD, and using monitoring/click-path analytics to prioritize work—achieved a 40% page-load reduction. Experienced operating microservices with RabbitMQ at scale, addressing retries/idempotency/observability and fixing duplicate-processing incidents with idempotent consumer patterns and DLQs.”

“Backend engineer who built an AI RAG quoting system for the fastener industry, reducing quote turnaround from weeks to ~30 minutes and raising retrieval accuracy to ~90% by solving a semantic-collision issue with a parent-document retrieval design. Strong in production AWS integrations (Cognito auth, S3 pre-signed uploads), performance optimization (multithreading/out-of-core), and real-time streaming (Kafka/Spark Kappa architecture achieving sub-second latency), plus Kubernetes logging and GitHub Actions CI/CD to ECR.”

“Backend/DevX engineer with startup experience who built internal JavaScript SDKs for POS integrations, including a daily GMV calculation feature standardized across multiple POS providers. Strong in performance debugging (used Jaeger to resolve legacy WebSocket bottlenecks) and developer enablement—built a cronjob migration tool (ArgoWorkflow to internal platform) with documentation that let teams migrate in ~30 seconds, plus handled on-call and internal support.”

“Built and deployed an enterprise RAG application at Centene to help clinical teams retrieve insights from large internal policy document sets, cutting manual research by 30–40%. Implemented custom domain-adapted embeddings (SageMaker + BERT transfer learning) and hybrid retrieval (BM25 + Pinecone) to drive a 22% relevance lift, and ran the system in production on AWS EKS with CI/CD, MLflow, and Prometheus monitoring (99% uptime, ~40% latency reduction).”

“Python backend engineer who owned an end-to-end Django/DRF authentication and account-management module (JWT, RBAC, email verification) and optimized token validation performance. Has hands-on Kubernetes + Helm delivery with GitOps via ArgoCD (multi-environment app-of-apps, drift detection/rollback) and has supported a cloud-to-on-prem migration using staged testing and phased cutover. Also built and scaled a Kafka-based real-time user activity tracking pipeline with reliability and backpressure controls.”

“AI/ML engineer (Merkle) with hands-on experience deploying RAG-based LLM applications and real-time recommendation engines into production. Strong in cloud/on-prem architectures, GPU autoscaling, caching, and network optimization—delivered measurable latency reductions (40–70%) and improved retrieval relevance by systematically benchmarking chunking/embedding configurations and validating pipelines via CI/CD.”