Pre-screened and vetted.
Intern Software Engineer specializing in GenAI and backend systems
Mid-level Backend/Distributed Systems Engineer specializing in cloud-native data pipelines
Mid-level Software/DevOps Engineer specializing in AI, cloud infrastructure, and LLM systems
Mid-level Cloud and DevOps Engineer specializing in AWS infrastructure and platform automation
Mid Software Engineer specializing in backend systems and cloud platforms
Junior Full-Stack Software Engineer specializing in web, mobile, and AI applications
Intern AI/Software Engineer specializing in LLM agents and full-stack automation
Mid-Level Full-Stack Software Engineer specializing in FinTech and AI risk scoring
Intern Software Engineer specializing in systems programming and game development
Junior Software Development Engineer specializing in AWS backend and distributed systems
Mid-level GPU Software Engineer specializing in high-performance parallel computing
Junior Software Engineer specializing in backend, distributed systems, and AI infrastructure
“Full-stack engineer with hands-on experience spanning real-time AI products, large-scale payments migration, internal research infrastructure, and open-source ML tooling. Particularly compelling is the mix of low-latency React/Node/TypeScript systems work, zero-downtime migration of 50,000 accounts across 12 regions, and proactive contributions to Kubeflow build and security reliability.”
Senior Software Engineer specializing in Cloud, Zero Trust, and Enterprise Platforms
“Zero Trust security product lead focused on UI/API delivery, stability, and customer adoption at enterprise scale, including deployments serving 1200 customers. Stands out for hands-on production debugging across the full stack, customer-facing incident ownership, and a pragmatic approach to turning failures into automated regression coverage.”
Mid-level Software Engineer specializing in LLM agents and full-stack systems
“At Esri, the candidate is building a production LLM-powered WebGIS AI framework that embeds an AI assistant into web maps and routes natural-language requests into ArcGIS JavaScript SDK functions via a LangGraph-orchestrated, multi-agent system. They emphasize production reliability and scale (strict tool calling/JSON, live schema validation, query guardrails) and rigorous evaluation/observability using LangSmith, offline prompt datasets, and latency/tool-call accuracy tracking.”
Intern Software Engineer specializing in FinTech and AI platforms
“Systems-focused engineer who built an OS kernel with multithreading, priority scheduling, system calls, and synchronization primitives, and debugged race conditions end-to-end. While not yet hands-on with ROS/SLAM, they clearly connect low-level concurrency and scheduling decisions to deterministic, reliable robotics-style real-time workloads.”
Intern Software Engineer specializing in distributed systems and backend infrastructure
“Backend engineer with deep experience building event-driven logistics systems (orders, warehouse execution, real-time delivery tracking) using Spring Boot/PostgreSQL/Redis and strong observability (Prometheus/Grafana). Led a zero-downtime migration from monolithic MySQL to a sharded architecture for ~2M users with dual-write, checksum validation, and fast auto-rollback, and has strong security expertise including PostgreSQL RLS for multi-tenant SaaS and robust OAuth/JWT handling.”
Intern Software Engineer specializing in AI/ML and full-stack development
“Full-stack engineer with fintech and AI product experience: built HuddleAI end-to-end on Firebase/React, including a serverless LLM meeting-intelligence pipeline (FFmpeg + Google Speech-to-Text + GPT-4 with schema validation) and Slack notifications. At Gemini, owned a Postgres/Scala workflow change for wire deposit approvals that cut blocked registrations by 60% and emphasized correctness/compliance in UK/EU transaction-state UI.”
Intern Software Engineer specializing in systems and full-stack web development
“Open-source contributor to a JavaScript visualization library who focused on runtime/rendering performance—eliminating unnecessary full redraws via memoization and diff-based updates validated with Chrome profiling. Also strengthened the project’s developer experience by adding TypeScript definitions, writing practical documentation, building minimal example apps, and handling community issues with reproducible debugging and public fixes.”