Pre-screened and vetted.
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.”
Junior Full-Stack Software Engineer specializing in AI-powered web applications
“Startup-focused engineer who has shipped Python backend features, AI integrations, and Playwright automation for products including an AI coaching platform and hiring workflow tools. Stands out for working through ambiguous zero-spec environments, hardening flaky Firebase-authenticated test flows, and designing practical fallback paths when AI outputs are unreliable.”
Junior Software Engineer specializing in AI, voice, and full-stack product engineering
“Product-minded full-stack engineer from SuperU who built AI voice-agent infrastructure end-to-end, from React/TypeScript campaign UIs to a forked n8n orchestration backend and Postgres multi-tenant data model. Stands out for shipping quickly in ambiguous startup environments, debugging deep reliability issues across layers, and delivering measurable gains like activation rising from 20% to 70%+ and call drops falling below 0.5%.”
Junior AI/Software Engineer specializing in NLP, RAG, and resume parsing
“Backend/AI engineer who built and refactored a production RAG system over IRS Form 990 filings for 60 nonprofits, using a dual-path architecture (deterministic financial ranking + TF-IDF semantic retrieval) to keep latency sub-2s and reduce hallucinations. Demonstrates strong API craftsmanship in FastAPI (contract-first, OpenAPI-driven) plus production-grade security for multi-tenant systems (JWT, RBAC, Supabase-style RLS) and careful migration practices (feature flags, traffic mirroring, incremental rollout).”
Junior Software Engineer specializing in automation and full-stack development
“Backend-focused engineer who built a time-sensitive data retrieval system for a source with no public API, using an AWS EC2-hosted persistent browser session plus a PostgreSQL TTL caching layer—cutting manual retrieval by 99% and achieving sub-10-second average retrieval. Emphasizes production security (Secrets Manager, encryption, IP allowlisting, rate limiting) and robustness via testing and edge-case handling (atomic file operations).”
Mid-level Frontend/Full-Stack Engineer specializing in React and scalable web apps
“Frontend-focused engineer who leads end-to-end delivery of high-performance React + TypeScript products, including legal-tech client platforms and a large-scale case management dashboard handling thousands of records. Strong in SEO for SPAs, strict code quality automation, and performance work (Lighthouse 95+, 40% FCP reduction), plus disciplined rollout practices using LaunchDarkly, canary releases, and Sentry monitoring.”
Senior Mobile & Full-Stack Developer specializing in cross-platform apps and AWS
“Frontend/mobile engineer with iOS and React/TypeScript experience who built an app (Tokidos) from proof-of-concept to production at Neuronic Works Inc. Focuses on scalable architecture (MVC/MVVM, feature-based modular structure), performance improvements (React Query, render optimization), and fast, low-risk delivery using QA scenarios and feature-flagged rollouts across web and mobile.”
Junior Frontend Developer specializing in React/TypeScript for SaaS and e-commerce
“Frontend developer (~2 years experience) who has built user-tier-based UI logic (BannerRotator) and shipped a KYC workflow in a fast-paced, regulated crypto/e-commerce context. Emphasizes modular React + TypeScript patterns, scenario-driven QA documentation in Notion, and codebase modernization (TypeScript rewrites and legacy hook updates).”
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 Full-Stack Software Engineer specializing in Java microservices and cloud-native delivery
“Built and shipped a production LLM feature that explains DSA problems with real-life explanations, using Grok with automatic failover to OpenRouter (and multiple backup models) to avoid user-facing failures. Improved cost efficiency by implementing difficulty-based token budgets and iterated prompt quality via structured constraints and an in-app feedback mechanism, reporting satisfaction across 38 users.”
Mid-level Data Engineer specializing in cloud ETL and big data pipelines
“Data engineer focused on building reliable, production-grade pipelines and data services end-to-end, including a 50+ GB/day pipeline ingesting from APIs/files into Snowflake with PySpark/SQL transformations. Emphasizes strong data quality controls, monitoring/retries, and performance optimization, and has also shipped a Python data API with caching and backward-compatible versioning.”
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.”
Junior AI Full-Stack Engineer specializing in LLM automations and RAG systems
“Built and shipped a production LLM-powered customer support assistant using a Python/FastAPI backend with RAG (embeddings + vector search) over internal docs and product/operational data. Instrumented the system with logging/metrics and ran continuous eval loops; post-launch improvements focused on retrieval quality (chunking/ranking) and performance/cost tradeoffs (query classification, caching, validation guardrails).”
Entry-level Full-Stack Software Engineer specializing in .NET, React, and cloud systems
“Full-stack developer with .NET and cloud-based development experience who has built a practical AI-assisted engineering workflow using Copilot, Claude, and GPT across coding, debugging, testing, and review. Stands out for using AI to accelerate delivery while still applying careful validation and human judgment for high-impact performance and security decisions.”
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.”
“Unity game developer who implemented a swipe-based pack-slicing minigame in "Herois da Fruta," improving responsiveness by evaluating both swipe start and end positions. Has multiplayer AR experience on "ARcade Sports" using Photon Unity Network to sync four AR devices, including coordinating AR anchors with online communication and camera/world alignment. Prefers collaborative teams and a 9-to-5 schedule; targets €17k–€20k depending on responsibilities and benefits.”
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.”
Junior Full-Stack Software Engineer specializing in cloud-native web apps and APIs
“Built a voice-driven desktop assistant for users with mobility impairments, integrating Whisper and Google Gemini and adding voice-authentication via speaker embeddings for secure command execution. Has hands-on experience with AWS serverless/microservices patterns (Lambda, S3, CloudFront, CloudWatch) and CI/CD, plus built an internal MySQL-to-MongoDB migration tool used by the CTO and dev team with an emphasis on safe, low-impact data transformation.”
Mid-level Machine Learning Engineer specializing in real-time AI and data platforms
“ML/NLP engineer who has built production systems end-to-end: a real-time recommendation platform (100k+ profiles) using BERTopic-style clustering and a RAG-based news summarization/recommendation stack with ChromaDB. Strong focus on scaling and reliability (GPU batching, Redis caching, Kafka ingestion, Docker/Kubernetes, Prometheus/Grafana) and on maintaining model quality over time via drift monitoring and retraining triggers.”
Mid-level Full-Stack Software Engineer specializing in cloud-native web apps and AI agents
“Full-stack system analyst/programmer at PeakPlay Sports (startup) who built an AI "coach" product end-to-end in ~2 months, using a LangGraph-orchestrated multi-agent architecture with a FastAPI backend. Shipped production RAG grounded in athlete history (OpenAI embeddings + vector store) with guardrails and a structured eval loop (golden set + LLM-judge + human review) to improve engagement and reduce hallucinations.”
Mid-level Full-Stack Python Developer specializing in AI/ML and backend APIs
“Python/Django backend engineer with open-source experience upgrading Archivematica to Django 4.2 LTS, including resolving a tricky breaking change in datetime parsing by implementing a preservation-safe legacy timestamp conversion layer. Also built a cost-efficient, reproducible Small Language Model (Microsoft Phi-3) fine-tuning pipeline that turns CSV product data into a domain-specific searchable Q&A chatbot, with emphasis on memory optimization and overfitting prevention.”
Intern Network/Applied Engineer specializing in cloud security and Kubernetes
“Security-focused engineer with hands-on experience implementing and troubleshooting security tooling (including an open-source SIEM) and integrating SCA/container scanning into AWS/EKS and GitHub Actions pipelines. Demonstrates strong cloud security fundamentals (least-privilege IAM, IRSA, private subnet/VPC design, CloudTrail/GuardDuty) and can translate security-usability tradeoffs (e.g., password policy and 2FA) to different stakeholders.”
Mid-Level Software Engineer specializing in game development and full-stack systems
“Backend-focused developer who built a Python 4v4 matchmaking system using win/loss history plus an Elo rating model, validating and tuning it against a dataset of ~50 real games. Previously worked at Advanced Logistics Management building time-sensitive agriculture-site modules in a small dev team, coordinating work via Jira/Git and drafting documentation for a potential migration from XAMPP/CodeIgniter/Bluehost to Azure.”
Junior Full-Stack Software Developer specializing in React, .NET, and Firebase
“Frontend engineer focused on scalable React + TypeScript dashboards and workflows, using feature-based architecture and a reusable component/hook approach. Has hands-on experience improving performance in table-heavy admin UIs (pagination, lazy loading) and shipping major features quickly with staging/manual QA, gradual rollouts, and rapid iteration based on production feedback.”