Pre-screened and vetted.
Senior Full-Stack Developer specializing in MERN, cloud platforms, and LLM-powered applications
Mid-Level Full-Stack .NET Engineer specializing in cloud, APIs, and data analytics
Mid-level Generative AI Engineer specializing in LLMs, RAG, and NLP systems
Junior Software Engineer specializing in ML inference infrastructure
Junior Full-Stack Software Engineer specializing in backend, cloud, and AI systems
Mid-level Full-Stack Engineer specializing in SaaS, HR Tech, and distributed backend systems
Mid-level Python Backend Engineer specializing in AWS cloud-native APIs
Senior Full-Stack Engineer specializing in Python, AI, and LLM-powered platforms
Staff/Lead DevOps & Site Reliability Engineer specializing in cloud infrastructure and Kubernetes
Junior Software Engineer specializing in AI/ML and full-stack applications
“AI/backend-focused builder who has shipped two distinct applied AI products: a game discovery platform with vector search + RAG chat, and an AI accounting platform for small businesses. Stands out for combining product discovery with hands-on system design, including sub-100ms retrieval performance, privacy-conscious financial workflows, and measurable impact like 58% compute-time reduction and support for 24,000+ user profiles.”
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 AI/ML Engineer specializing in anomaly detection, data tooling, and cloud-native systems
“Backend/platform engineer who built an LLM-driven QA automation system (“mockmouse”) using a Flask orchestration microservice, Socket.IO real-time updates, Redis caching, and strict Pydantic schemas to turn prompts into reliable action graphs and automated browser tests. Has hands-on Kubernetes delivery experience (Docker/Helm/Jenkins) and has supported large migration programs, validating ETL cutovers with 1M+ synthetic records and rigorous output comparisons; also built event-driven monitoring/anomaly detection streaming into Grafana.”
Intern Software Engineer specializing in AI, cloud, and backend systems
“Candidate has internship and graduate-project experience building AI agents, including a production log-analysis assistant using a lightweight agentic/RAG-style workflow with local GPT training and validation against historical logs. They also worked on Android/iOS game build and release processes in a Unity-based robot racing game environment, and highlight measurable LLM outcomes including 80% analysis accuracy, 2-5 second latency, and 50% cost reduction.”