Pre-screened and vetted.
Senior Software Engineer specializing in distributed systems and cloud-native platforms
“Backend-leaning full-stack engineer with experience at Walmart, Qualtrics, and American Express, shipping secure partner-facing API platforms and internal monitoring dashboards. Strong in AWS production operations (ECS/Fargate, RDS/Postgres, CloudWatch) plus rigorous testing/security practices, with measurable delivery and performance improvements (35% faster releases; ~30–40% latency reductions).”
Mid-level Data Engineer specializing in cloud lakehouse/warehouse pipelines
“Data engineer with HCA Healthcare experience building and operating end-to-end AWS-based pipelines for clinical and operational reporting (50–100 GB/day), serving curated data into Redshift/Snowflake for Power BI/Tableau. Emphasizes production reliability (Airflow SLAs/retries/alerting, logging/observability) and strong data quality controls (reconciliations, schema/null/duplicate checks), and has shipped versioned REST APIs to expose warehouse data to downstream systems.”
Senior Data Engineer specializing in cloud data platforms and real-time analytics
“Data engineer (Credit One) who built and owned real-time financial transaction and credit risk/fraud data systems end-to-end on AWS + Snowflake. Delivered high-scale pipelines (150k events/hour; ~2TB/week), raised data accuracy to 99%, and cut Snowflake costs 42% while adding strong observability, schema-drift handling, and production-grade APIs/documentation.”
Mid-Level Full-Stack Software Engineer specializing in cloud-native web platforms and observability
“Built and shipped production LLM agents including an AI patient appointment assistant for Kyron Medical that automated specialist matching and end-to-end booking with email/SMS confirmations and a voice mode. Strong focus on production reliability (double-booking prevention with DB constraints and pre-write checks), deterministic multi-step orchestration with LangGraph, and rigorous monitoring/evaluation using LangSmith trace replay for prompt regression testing.”
Mid-level Software Engineer specializing in full-stack cloud and backend systems
“Full-stack JavaScript engineer (React/Node/Vue) who has operated like a maintainer by owning an internal component library with Storybook-style examples, documentation, and non-breaking versioning. Demonstrated strong performance engineering on a source code review service—profiling bottlenecks, fixing N+1 queries, adding caching, and trimming payloads to cut latency (e.g., ~100ms to <50ms) while rolling out incremental, test-backed improvements.”
Senior AI/ML Engineer specializing in supply chain and healthcare systems
“Built and deployed AcademiQ Ai, a production LLM-based teaching assistant using GPT/BERT with RAG (LangChain + Pinecone) to handle large student notes and generate adaptive explanations/quizzes. Demonstrated measurable retrieval-quality gains (18% precision improvement, 22% less irrelevant context) by tuning similarity thresholds and chunking based on user satisfaction signals. Also orchestrated terabyte-scale, real-time demand forecasting pipelines using Airflow and Kubeflow on GCP with strong monitoring, shadow deployment, and feedback-loop practices.”
Mid-level Full-Stack .NET Engineer specializing in AI-integrated enterprise applications
“Full-stack engineer who has owned an operations/reporting dashboard end-to-end, spanning React/TypeScript frontend architecture, ASP.NET Core APIs, and SQL data access. Stands out for combining strong UI performance optimization with pragmatic backend decisions, post-launch monitoring, and 0→1 startup platform building that improved API speed by 35% while supporting 2,000+ transactions per hour.”
“Frontend-leaning full-stack engineer with deep experience building real-time financial trading platforms at Bank of America. They led modernization of a global markets product by consolidating three legacy apps into a single React/Next.js platform, built WebSocket-driven market data experiences, and helped drive shared component libraries and engineering standards used across multiple teams.”
Mid-level DevSecOps/Cloud Engineer specializing in AWS platform engineering and Kubernetes
“Infrastructure/Platform engineer with deep production ownership of large IBM Power/AIX estates (70 LPARs, dual VIOS, HMC across two data centers), including live DLPAR tuning and PowerHA clustering for Oracle/WebSphere. Also brings modern DevOps/IaC experience—built GitHub Actions pipelines deploying to Kubernetes with OIDC/Vault secrets and implemented Terraform to provision AWS EKS/VPC/IAM/ALB/RDS with drift detection and controlled rollouts.”
Mid-Level Software Engineer specializing in backend systems and CRM integrations
Senior Backend Engineer specializing in Healthcare IT and cloud microservices
Mid-level Data Engineer specializing in scalable real-time data platforms
Senior Software QA Engineer (SDET) specializing in UI, API, and end-to-end test automation
Senior QA Automation Engineer specializing in web, mobile, API, and data validation testing
Mid-level Full-Stack Engineer specializing in AI, media, healthcare, and e-commerce
Mid-level Full-Stack Engineer specializing in backend systems and FinTech
Entry-level Software Engineer specializing in full-stack web and systems development
Executive engineering leader specializing in consumer AI and full-stack platforms
Senior Software Engineer specializing in backend, full-stack, and ML-integrated systems
Mid-level Data Engineer specializing in cloud ETL/ELT, Spark, and streaming pipelines
Junior Full-Stack Software Engineer specializing in microservices and AI chatbot platforms
Mid-level Software Developer specializing in cloud-native FinTech microservices
Mid-level Data Engineer specializing in AWS cloud data platforms and streaming analytics