Pre-screened and vetted.
Junior Full-Stack Developer specializing in AI integrations and LLM research
Mid-Level Software Engineer specializing in distributed microservices and cloud-native systems
Junior Full-Stack Software Engineer specializing in cloud-native microservices
Junior AI Engineer specializing in LLMs, RAG systems, and MLOps
“Robotics software engineer who built an end-to-end system ("justmatrix"), focusing on multi-agent orchestration and a multi-RAG retrieval backend/API. Has hands-on ROS experience, including a custom node for reliable high-frequency sensor data routing, plus deployment automation using Docker, Kubernetes, and CI/CD.”
Mid-Level Full-Stack Engineer specializing in React, TypeScript, and Node.js
Junior Software/AI Engineer specializing in LLM agents and RAG systems
Executive Founder-CTO specializing in AI agents and distributed systems
Entry-level Software Engineer specializing in backend and full-stack systems
“Built production-style backend and AI systems across internship and project work, including a real-time sports platform backend and a Smart Email Assistant using GPT-4. Stands out for combining classic backend performance engineering with practical LLM workflow design, including measurable latency improvements, high uptime, and debugging of non-deterministic model behavior.”
Mid-level Robotics & Embedded Systems Research Engineer specializing in edge AI for precision agriculture
“Robotics lead engineer (PhD/agriculture research context) who built and iterated a three-unit, wirelessly coordinated greenhouse data-collection robot—solving real-world alignment and comms reliability issues by redesigning the rail/gear system and moving from RF to ESP Wi-Fi with MAC-addressed control. Strong embedded C/C++ background with full-stack robot control implemented from scratch; beginning exposure to ROS 2 via an upcoming field deployment.”
Junior Backend Software Engineer specializing in API-driven systems
“Backend engineer focused on Python/FastAPI who has designed and evolved an API-driven platform with an emphasis on clean contracts, data integrity, and scalable service boundaries. Demonstrated production-minded reliability work by addressing partial writes/retry failure modes with idempotency and validation, eliminating duplicate/corrupted records, and has implemented layered security including Supabase-managed auth, RBAC, and row-level security.”
Mid-level Software Engineer specializing in AI automation and backend systems
“Hands-on automation and QA-focused developer using AI agents, MCP tools, and LLMs to streamline business workflows. Built agents for automated Jira bug logging, executive summary dashboards, and a rule-explainer that translates technical business rules into plain language for end users, while also supporting Selenium-to-Playwright migration and guiding peers on AI implementation.”
Intern Application Security Engineer specializing in cloud and container security
“Application security engineer/advisor with hands-on experience securing AWS-based, containerized services and embedding SAST/DAST/SCA and container scanning into GitHub/GitLab CI/CD. Drove measurable outcomes (50% faster vuln triage, 40% fewer misconfigs) and has deep operational troubleshooting experience in Kubernetes (agent failures due to CPU throttling/network policies), plus pragmatic strategies to reduce developer friction and handle API rate limits.”
Mid-level Quantitative Developer specializing in low-latency trading systems
“Backend/ML engineer with deep fintech and marketplace experience: built a real-time financial analytics + algorithmic trading platform (Python/Postgres/Kafka/Redis) and drove major DB performance wins (10x faster analytics; sub-10ms response consistency). Also shipped an end-to-end ML recruitment matching platform (scraping/ETL/modeling/Django deployment) with reported 92% matching accuracy, and emphasizes production reliability via monitoring, blue-green deploys, and robust workflow error handling.”
Senior Full-Stack/Backend Engineer specializing in APIs, distributed systems, and AI integrations
“AI/backend engineer who has built and scaled production LLM-powered SaaS features (document assistant + compliance review agent) on a Node.js/TypeScript + Postgres/Redis stack deployed to GCP Kubernetes. Demonstrates strong production reliability chops—async queueing, autoscaling, observability, and database tuning—with quantified wins (p95 latency -60%, query 4s to <200ms) and robust AI guardrails (strict RAG, schema validation, citations, HITL).”
Entry-Level Full-Stack AI Engineer specializing in RAG pipelines and enterprise SaaS
Junior Full-Stack Software Developer specializing in cloud-native apps and data/AI
Entry-level Software Engineer specializing in AI/ML and cloud backend systems
Junior Software Development Engineer specializing in cloud and full-stack development
Mid-level Full-Stack AI Engineer specializing in RAG systems and intelligent automation
Junior Full-Stack Software Engineer specializing in Spring Boot, React, and mobile apps