Pre-screened and vetted.
Mid-level DevOps Engineer specializing in cloud infrastructure and CI/CD automation
Junior Full-Stack & Machine Learning Engineer specializing in observability tools
Entry-Level Full-Stack Software Engineer specializing in Java, Python, and JavaScript
Junior Backend/Full-Stack Software Engineer specializing in scalable APIs and cloud platforms
Junior Software Engineer specializing in Python microservices and AWS
Mid-level Python Developer specializing in cloud-native APIs and microservices
Mid-level Python Backend Engineer specializing in microservices and AWS
Mid-level Full-Stack Developer specializing in Python, React, and cloud-native microservices
Mid-level Systems Architect specializing in institutional trading infrastructure
Entry Backend Software Engineer specializing in Python/FastAPI and cloud-native APIs
“Backend engineer who built and evolved a low-latency document search platform (C++/gRPC on Kubernetes with a vector database), emphasizing resilience under concurrent load through strict deadlines, retries, idempotency, and observability. Also experienced building secure, frontend-friendly FastAPI services (Pydantic + JWT) and executing safe incremental refactors using feature flags and parallel validation.”
Mid-level Backend/Agentic AI Engineer specializing in GenAI automation and RAG systems
“Built and shipped a production AI-driven privacy automation system that autonomously navigates data broker sites to submit opt-out/data deletion requests end-to-end, including robust CAPTCHA detection/solving (e.g., reCAPTCHA/hCaptcha/Cloudflare) via 2Captcha. Experienced in orchestrating stateful LLM agent workflows with LangGraph and hardening them for production with strict state management, retries/fallbacks, validation layers, and database-backed observability/audit logs, collaborating closely with legal/compliance stakeholders.”
Junior AI/ML Engineer specializing in LLM systems and personalization
“Backend engineer who built and scaled AmazonProAI, a multi-tenant SaaS platform for Amazon sellers, using a modular Django/DRF monolith with strict seller-level isolation and security controls. Led a controlled SQLite-to-PostgreSQL migration and hardened bulk Excel ingestion with idempotency and data integrity constraints to prevent duplicate metrics and noisy alerts while keeping the system ready for future service extraction.”
Entry-level Software Engineer specializing in systems, graphics, and game development
“Hands-on builder who has shipped multiple self-directed Python automations, including a PySide6 desktop app that uses LLMs for job search and resume matching, plus AWS-hosted notification workflows and Chromium-based browser automation. Particularly interesting for roles involving AI integrations, automation, and reliability work because they speak concretely about schema drift, hallucination mitigation, observability, threading, and flaky auth/session handling.”
Junior Full-Stack Engineer specializing in web and mobile product development
“Built a production shared authentication service at Tilli using Python and Better Auth, packaging it for reuse across multiple applications. Shows strong reliability instincts through edge-case testing, logging, session-state debugging, and iterative hardening of cross-app auth flows in production.”
Mid-Level Software Engineer specializing in cloud data platforms and CI/CD
“AI/LLM engineer who has owned end-to-end production delivery of multi-agent RAG systems on Azure (React + FastAPI + data pipelines + Terraform), including rigorous evaluation/monitoring and reliability guardrails. Shipped an AI-driven observability root-cause analysis assistant that reduced MTTR ~30%, cut alert noise ~20%, and reached ~70% adoption in the first month; also built a clinical document Q&A system with citations and compliance-oriented controls.”
Junior Full-Stack Software Engineer specializing in AI and web applications
“LLM/AI backend engineer with hands-on experience taking customer LLM prototypes into production using FastAPI, containerization, CI/CD, and OpenTelemetry-based observability. Demonstrated measurable impact by cutting LLM costs ~40% and reducing workflow errors ~50% through schema-enforced outputs, better tool definitions, retries, and prompt/model optimization; also supports pre-sales via technical discovery and rapid integration demos.”
“Backend/infrastructure engineer in the EBS org focused on global server lifecycle and fleet reliability. Led a major modernization from manual, ticket-driven recovery to centralized Python services and operator tooling with DynamoDB-backed state, strong auth/allowlisting, and CloudWatch monitoring, plus an AWS Glue/S3/SNS data pipeline to join server and hardware datasets for global operational querying and automated recovery.”