Pre-screened and vetted.
Mid-level Software Engineer specializing in ML deployment and full-stack development
Mid-level Full-Stack Software Engineer specializing in streaming media and real-time systems
Entry-level Full-Stack Engineer specializing in AI-powered backend systems
Mid-level Software Engineer specializing in backend, data platforms, and distributed systems
Senior Full-Stack Software Engineer specializing in cloud platforms and AI evaluation
Mid Software Engineer specializing in backend and AI-driven FinTech systems
Senior Full-Stack Engineer specializing in AI-powered enterprise applications
Mid-Level Full-Stack Software Engineer specializing in Java/Spring, React, and AWS
“Backend/full-stack engineer (5+ years) with Shopify experience integrating LLM/RAG workflows into production APIs. Owned a Python TensorFlow Serving inference pipeline connected to Java microservices via gRPC, optimizing tail latency at ~10k concurrent load and improving retrieval relevance with embedding and evaluation work. Strong Kubernetes/EKS + GitOps/CI/CD background, including monolith-to-microservices migrations and event-driven streaming patterns.”
Staff Full-Stack Engineer specializing in AI platforms and Healthcare IT
“Senior full-stack engineer with seed-stage fintech experience who has led payment API development, implemented compliance-related standards, and built production systems across React, Go, Python, Node.js, and PostgreSQL. Notable impact includes enabling a first major client launch, reducing logistics response times by 30%, improving page load times by 40%+, and cutting analytics report generation from minutes to seconds.”
Senior Full-Stack Engineer specializing in FinTech and cloud-backed web platforms
“Full-stack engineer with strong AI systems and B2B SaaS experience across BrightOps, Zapier, Nordstrom, and Calendly. They’ve owned architecture for an AI-powered tutoring platform, improved retrieval quality with a hybrid vector-plus-keyword approach, and built Go services processing over 1 million student events per day. Particularly compelling for teams building data-intensive, reliability-critical products with LLM, workflow automation, or compliance-oriented use cases.”
“Frontend-leaning full-stack engineer with Bank of America experience building production internal payment operations dashboards and modernizing legacy service integrations. Stands out for owning both design and implementation, from React/TypeScript UI architecture to Spring Boot APIs, with strong attention to performance, reliability, and production observability in complex financial systems.”
Senior Full-Stack Engineer specializing in AWS, Ruby on Rails, and JavaScript
Mid-level Full-Stack Developer specializing in AI-driven FinTech platforms
Mid-level Software Engineer specializing in AWS, full-stack development, and AI data systems
“Backend engineer who built a Python-based data profiling/statistics platform processing up to 50M rows and ~300 metrics, using a DAG execution model, multithreading, and smart caching to cut processing time by up to 70%. Also improved PostgreSQL query performance from 12s to 2s via indexing/query rewrites, integrated an LLM (LangChain + OpenAI) for explainable “chat with the pipeline” functionality, and designed an AWS EC2+SQS architecture for scalable, isolated per-user processing.”
Mid-level Full-Stack Software Engineer specializing in cloud, microservices, and React/Java
“Software engineer with experience at PayPal and JPMC building large-scale onboarding/account setup systems using React/TypeScript with Spring Boot/Node microservices and Kafka. Also built an Ignition-based SCADA monitoring tool at Mainspring Energy that became the default for manufacturing/test engineers by aggregating real-time telemetry and historical test data.”
Mid-Level Software Development Engineer specializing in interactive ad formats
“Has experience improving an ad server workflow by standardizing genre selection with templates, enabling reuse across multiple accounts and measuring success via hours of manual labor saved. Also delivered an internal technical demo on a device-metrics-to-AWS-CloudWatch logging workflow using whiteboarding and PowerPoint to onboard a new team.”
Mid-level Full-Stack Software Engineer specializing in FinTech microservices
“Robotics software engineer who has built end-to-end pipelines spanning backend/data processing through model interfaces and hardware integration. Has hands-on ROS2 experience building Python nodes and debugging real-time behavior via profiling, publish-rate tuning, and latency fixes, plus experience standardizing multi-robot communication with QoS adjustments. Uses Gazebo simulation and Docker/CI/CD to catch integration issues early and speed iteration.”
Mid-level Full-Stack Engineer specializing in scalable APIs, cloud infrastructure, and GenAI apps
“Backend/platform engineer with experience across edtech, logistics, and AWS internal systems—owned a production course recommender end-to-end (model serving + APIs + caching/observability), delivering +30% CTR and -20% latency. Has scaled real-time delivery visibility/rerouting on Kubernetes/EKS to sub-200ms P95 during demand spikes and built billion-events/day telemetry pipelines on AWS (Kinesis Firehose, Lambda, S3, Redshift) with schema evolution, dedupe, and replay support.”
Mid-Level Full-Stack Software Engineer specializing in Java/Spring, AWS, and Angular
“Amazon engineer who owned customer-facing Alexa features and built automation-heavy delivery practices (API/service-level testing in CI/CD) to ship quickly without sacrificing stability. Also built an internal self-service feature management/beta access platform (Angular + Spring Boot + event publishing) that replaced a multi-team ticket workflow with instant, auditable operations, and has deep microservices/Kafka experience with strong observability and reliability patterns.”
Senior Full-Stack Developer specializing in cloud-native microservices
“Java full-stack developer who has owned data-intensive, customer-facing and internal web products end-to-end (React/Angular + Spring Boot), including CI/CD and production support. Demonstrates deep microservices experience with RabbitMQ/event-driven architecture, idempotency, DLQs, and compensating logic to maintain reliability and data consistency at scale, plus a track record of replacing spreadsheet-based ops reporting with an adopted real-time internal tool.”