Pre-screened and vetted.
Senior Full-Stack Developer specializing in Python/Django and cloud-native web apps
Senior Frontend/Full-Stack Developer specializing in FinTech and high-performance web apps
Senior Frontend Developer specializing in React, performance optimization, and data-heavy UIs
Senior Full-Stack & Machine Learning Engineer specializing in scalable SaaS and cloud AI
“Frontend engineer who led an enterprise self-serve analytics dashboard end-to-end using a micro-frontend React/TypeScript architecture with strong integration discipline (contracts, CI gates, ADRs). Demonstrated measurable performance wins (35% faster LCP) through code splitting, lazy loading, and tighter Redux subscriptions, and uses feature flags plus automated E2E coverage for controlled rollouts.”
Mid-level Web Developer specializing in React and TypeScript
“Frontend developer (self-described intermediate/junior+) who built and released an end-to-end portfolio game (“Dot and Boxes”) in ~3 weeks using React state + Redux, including an in-app guided tour. In a prior role, worked on a full UI + flow redesign for a long booking workflow, focusing on reusable components and integrating Redux while dealing with complex/duplicated state and limited access to external designers via a PM intermediary.”
Junior AI/ML Engineer specializing in Python ML, NLP, and model deployment
“Built and productionized a real-time social-media sentiment analysis system used by a marketing team to monitor brand/campaign performance. Experienced in orchestrating LLM workflows with LangChain (validation → prompting → parsing → post-processing), plus monitoring, retraining, and RAG-style retrieval using embeddings/vector stores to keep outputs reliable over time.”
Mid-Level Software Engineer specializing in Java microservices and event-driven systems
“Backend-focused engineer with experience spanning research and healthcare: owned a Python/SQL data pipeline that transformed vulnerability-fix code data from SQLite into model-ready JSON for LLM analysis. Also deployed Dockerized Spring Boot microservices to Kubernetes with Jenkins CI/CD and built Kafka-based real-time event streaming (appointment/report events) with idempotent consumers to avoid duplicate processing.”
Mid-Level Full-Stack Software Engineer specializing in web platforms, cloud, and test automation
“Full-stack engineer with hands-on ownership of production systems, including a Kafka-based notification/alerting platform (Node.js + React) deployed on AWS with Docker/GitHub Actions, achieving ~95% email delivery reliability. Demonstrates strong operational maturity (observability, CI/CD, zero-downtime migrations) and experience shipping in ambiguous environments (SJSU project) with evolving requirements.”
Mid-level Data Engineer specializing in ETL pipelines on GCP
“Full-stack engineer from Larix Technologies who led a Next.js migration feature: an internal real-time workflow status dashboard built with App Router/TypeScript using server components for initial render and client polling for live updates. Demonstrates strong post-launch ownership—monitoring latency/error rates, adding caching and payload reductions, and optimizing Postgres queries/indexes—plus experience building durable RabbitMQ-based message routing workflows with idempotency, retries, and dead-letter queues.”
Mid-level Full-Stack & Cloud Engineer specializing in backend, AWS infrastructure, and DevOps
“IBM Power/AIX engineer who has owned a large production estate (20+ Power9/Power10 frames and 400+ LPARs) with vHMC and dual-VIOS HA. Has hands-on incident recovery experience (NPIV/RMC issues, LPM restores) and PowerHA failovers, plus modern DevOps exposure using Terraform on AWS and CI/CD with GitHub Actions/Jenkins (including deploying AI/RAG and vision workloads).”
Junior Full-Stack Software Developer specializing in React, Node.js, and AWS
“Frontend engineer at WITT who led multiple end-to-end React/TypeScript products in fintech/e-commerce contexts, including a shopping cart with Stripe payments and a multi-step registration flow. Emphasizes scalable component architecture, strong QA (tests/reviews/linting), and performance work (lazy loading/memoization), plus disciplined rollout via feature flags and close product/design collaboration.”
Mid-level AI Engineer specializing in LLM agents, RAG, and data pipelines
“Built and productionized LLM-powered workflows that generate contextual insights from structured financial data, including prompt/retrieval design, data standardization, and reliability controls like rate limiting and batching. Also diagnosed and fixed real-time failures in an automated order validation system using logs/metrics, staging reproduction, edge-case handling, retries, and alerting, while supporting sales/customer teams with demos, scripts, and FAQs to drive adoption.”
Mid-level QA Engineer specializing in manual testing and API/OCR validation
“Manual QA tester with ~3 years of experience and a strong gamer/end-user mindset, aiming to transition into console game testing. Has provided UX-focused feedback to product leadership and prefers a collaborative, less-structured workflow (e.g., live testing with engineers in local environments to reduce downstream defects). Not yet familiar with console certification standards (TRC/XR/LOT) but highly motivated to learn.”
Junior Full-Stack Software Engineer specializing in AI-powered SaaS
“Full-stack engineer from an early-stage AI SaaS startup who owned and shipped a production AI-powered PDF document chat and sharing feature end-to-end (React/TS + Node + Postgres on AWS). Demonstrates strong product thinking through layered success metrics and tight feedback loops, plus hands-on reliability/observability work (CloudWatch, structured logging, alarms) and robust ingestion pipeline patterns (idempotency, retries, reconciliation).”
Mid-level QA Automation Engineer specializing in Playwright and cross-browser E2E testing
“QA automation engineer with strong end-to-end ownership of UI automation for financial transaction workflows, using Selenium/Playwright/Cypress and CI/CD gating. Improved suite robustness via UI-API validations, negative testing, and flake reduction (intercepts + data-testid), catching critical backend calculation issues before production and cutting regression runtime by 40%.”
Mid-level Full-Stack Software Engineer specializing in FinTech and real-time systems
“Full-stack product engineer with a strong real-time systems focus: built and rolled out a WebSocket-based notifications system (with robust reconnect/resync and event ordering protections) that cut update latency to under 200ms. Also owned a workflow automation platform backend in FastAPI (JWT/RBAC, versioned APIs, standardized errors), designed the PostgreSQL schema for workflows/tasks/executions, and operated deployments on AWS ECS Fargate with blue-green CI/CD and performance stabilization via caching and autoscaling.”
Mid-Level Software Developer specializing in cloud-native microservices, iOS, and ML deployment
“Backend engineer with production ERP experience deploying microservices and improving performance/reliability using a metrics-driven approach (logs, latency, error rates). Has hands-on cloud/hybrid operations across AWS and Azure with Docker/Kubernetes, and has resolved real-world mobile sync issues by tuning timeouts/retries and reducing payload sizes. Builds configurable Python services to deliver customer-specific behavior without destabilizing the core codebase.”
Intern Full-Stack/ML Engineer specializing in cloud-native web apps and LLM systems
“Machine learning lab assistant at Eastern Illinois University who productionized a voice-enabled conversational AI system: redesigned it with RAG, LoRA fine-tuning (including text-to-SQL), and safety guardrails, then deployed a scalable API supporting ~1,000 daily queries. Also partnered with customer-facing teams during a BlueFi internship by building demos/APIs and accelerating releases via Terraform + AWS CI/CD automation.”
Mid-Level Full-Stack Software Engineer specializing in AI agents and cloud platforms
“Backend/data engineer focused on climate/emissions data platforms, building production Python (FastAPI) microservices and AWS serverless/ETL pipelines (Glue/Athena/Lambda/EventBridge). Demonstrated strong reliability and observability practices plus measurable optimization wins, including cutting PostgreSQL query runtimes from minutes to seconds and reducing AWS costs from ~$6k/month to ~$400/month.”
Mid-level Unity Developer specializing in shared frameworks, tools, and gameplay systems
“Unity/C# game developer/designer who created a lobby “Race” minigame that incentivized core gameplay engagement; leadership reported roughly a $10k weekly revenue intake increase after release. Has foundational networking experience (sockets, REST) and self-taught Photon, and uses AI tools to quickly refresh and implement newer Unity systems like the Input System.”
Junior Software Engineer specializing in backend, cloud, and data pipelines
“Software engineer with demonstrated production performance wins (37% latency reduction) through SQL optimization, backend API redesign, and disciplined rollout practices (staging, feature flags). Experienced debugging distributed pipeline issues across infrastructure layers (memory pressure and network timeouts) and building AWS-based systems (Lambda + RDS) to handle request spikes, including work on a business-focused chatbot.”
Mid-level Mobile Front-End Developer specializing in React Native apps
“Mobile/frontend engineer with hands-on ownership of major app initiatives, including migrating a telecom app from Ionic to React Native using an MVVM architecture and Jest unit testing. Built complex airline app experiences in React + TypeScript (booking, seat maps, Stripe payments) and improved maintainability by replacing a complex Redux-like booking flow with a simpler Context-based system; experienced working both as a solo mobile developer and within Agile teams using Jira/Notion.”
Intern AI/ML Engineer specializing in LLMs, RAG, NLP, and MLOps
“Built and deployed a production RAG-based internal document Q&A system using LangChain, vector search, and a dockerized FastAPI LLM service. Focused on reliability by systematically reducing hallucinations and improving retrieval through prompt grounding/abstention strategies, chunking and top-k tuning, and iterative evaluation with logged metrics and manual validation.”