Pre-screened and vetted.
Mid-level Software Engineer specializing in full-stack and cloud-native backend systems
“Full-stack/backend-leaning engineer with hands-on experience building transaction-processing systems using React, TypeScript, Node.js, MySQL, and Spring Boot microservices. They have owned services in production on AWS EKS, diagnosed peak-traffic failures via CloudWatch, and driven architectural modernization to Kafka-based microservices that improved scalability, deployment speed, and reliability.”
Intern software developer specializing in full-stack and automotive software
“Built Moodify, an emotion-based music recommender, as a full-stack TypeScript project using React, Express, MongoDB, and Spotify APIs. Demonstrates hands-on ownership across frontend, backend, database design, production monitoring, and architectural refactoring, with measurable improvements in response time and engineering speed.”
Junior Software Engineer specializing in backend, data engineering, and cloud systems
“Backend-leaning full-stack engineer with strong infrastructure depth who has owned high-scale production systems end to end, including an event ingestion pipeline that reached 200k+ events per second with zero data loss after launch. Also has hands-on AI experience building a Bedrock-based multi-agent travel assistant with RAG, plus cross-stack healthcare work and business-process automation that cut manual effort by 90%.”
Senior Full-Stack Engineer specializing in FinTech compliance platforms
“Software engineer with MERN stack experience who says they have built enterprise and SaaS products, set up CI/CD pipelines using GitHub Actions and Jenkins, and created reusable UI components across an application. They also referenced using AI tools like Claude, GPT, Codex, and Cursor with agentic AI concepts, plus CloudWatch-based tracing and crash monitoring.”
Mid-level XR Developer specializing in real-time WebXR/Unreal/Unity systems
“UE5 Blueprint-focused gameplay/system designer who shipped an XR interactive experience (“Echoes of the Moon”), owning interaction logic, progression triggers, state management, and animation syncing through ship. Emphasizes modular component-based architecture with interfaces and data-table-driven tuning, plus strong profiling/optimization skills (refactoring Tick-heavy systems to event-driven) validated through 20–30 user playtests and mobile XR (Android) frame-budget constraints.”
Junior AI & Data Engineer specializing in LLM systems and analytics platforms
“Backend/ML engineer who built a job-search automation SaaS using a modular Selenium ETL pipeline, rigorous testing/observability, and a cost-optimized two-pass LLM ranking approach. Has led high-integrity data extraction from messy multi-city PDF records (95% integrity) and managed modular production rollouts for a 20+ engineer team, with a strong security focus (deny-by-default, row-level access control) in an AI-assisted grading platform.”
Intern Robotics Software Engineer specializing in SLAM and edge deployment
“Robotics software engineer who built a full LiDAR SLAM pipeline from scratch in C++ (ICP, pose graph optimization, loop closures) and validated it quantitatively against ground-truth datasets. Extensive ROS2 experience from academics and an internship building a localization system, plus practical deployment work using Docker across x64 and ARM edge devices; also trained RL policies for TurtleBots in Gazebo.”
Mid-level Full-Stack Software Engineer specializing in cloud-deployed web apps and APIs
“Software engineer who has shipped both core web platform features (secure user authentication/profile management) and production LLM systems. Built an internal documentation knowledge assistant using a full RAG pipeline (OpenAI embeddings, vector DB, semantic search, reranking) with evaluation loops and a scalable document-ingestion pipeline for PDFs/FAQs, iterating based on metrics and user feedback.”
Mid-level Robotics Software Engineer specializing in autonomous systems and perception
“Robotics software engineer with a Master’s in Robotics who built a digital twin of an excavator by creating a high-fidelity URDF (kinematics, joint limits, inertial properties) to stress-test controllers near saturation/limit conditions using ROS2 + MoveIt. Has hands-on ROS/ROS2 experience building perception (AprilTag/OpenCV) and sensor interface nodes (IMU/encoders/CAN), plus data-driven debugging and SLAM tuning for GPS-denied navigation using ROS bags and loop-closure validation.”
Mid-Level Full-Stack Software Engineer specializing in cloud microservices and data engineering
“Software engineer with robotics and data-platform experience from CVS Health, spanning Java/Spring Boot microservices, secure APIs, React dashboards, and Snowflake/SSIS ETL optimization. Hands-on ROS 2 developer who built real-time LiDAR obstacle-detection nodes, improved SLAM performance, and coordinated multi-robot communication using DDS, with simulation/testing via Gazebo and CI/CD deployments using Docker and Jenkins.”
Intern Robotics Software Engineer specializing in SLAM, perception, and motion planning
“Robotics software engineer with hands-on experience building Visual-Inertial SLAM and ROS2 sensor-fusion pipelines for autonomous warehouse forklifts (ArcBest), including rigorous calibration (AprilTags, Allan variance, temporal sync) and recovery features like pose injection. Also implemented RL-based local planning at RollNDrive using Isaac Sim with domain randomization to bridge sim-to-real, improving real-world navigation success back to ~90% after initial deployment.”
Mid-level AI Engineer specializing in LLM agents and RAG for health-tech
“Backend engineer with health-tech AI platform experience who designed a modular FastAPI/PostgreSQL architecture supporting real-time user data and swap-in AI workflows. Has hands-on production experience with observability (CloudWatch, structured logging, LangSmith/LangGraph/LangChain tracing), secure auth (OAuth2/JWT, RBAC, RLS), and careful data-pipeline migrations using parallel runs and rollback planning.”
Mid-level AI/ML Engineer specializing in financial risk, fraud analytics, and forecasting
“Built and productionized an LLM-powered financial intelligence and forecasting platform at Northern Trust using a RAG architecture (LangChain + Hugging Face + FAISS) with end-to-end MLOps (Docker/Kubernetes, Airflow, MLflow). Emphasized regulatory-grade explainability (SHAP/Power BI) and hallucination control (retrieval-only grounding), achieving ~30% forecasting accuracy improvement and ~65% reduction in analyst research time, with sub-second inference and 95% uptime on EKS/AKS.”
Senior Unity Developer specializing in mobile, VR, and AR games
“Unity/C# developer focused on Meta Quest VR simulations and indie game development; built a factory onboarding VR experience largely solo, including modular scenario orchestration, interaction systems, and branching NPC dialogue. Also created multiple Unity games in the last year and built reusable internal packages (game management + UI/screens), while using an AI-driven pipeline for rapid prototyping and 3D asset generation.”
Senior Unity 3D Developer specializing in mobile games, AR/VR, and architecture
“Unity gameplay engineer with experience across multiple genres (city builders, match-3, RTS) including implementing an open-world isometric fog-of-war system optimized via chunking and multithreading. Has shipped multiplayer features using Photon/UNet and has dealt with real-time synchronization/ownership conflicts, and also applies AI automation to speed up code reviews and improve Jira/merge request workflows.”
Mid-level Full-Stack Developer specializing in React, monorepos, and AWS
“Frontend/product engineer who has led end-to-end builds across automotive and healthcare: created a multi-tenant, high-performance Next.js luxury inventory platform and a secure, Stripe-powered sick-note workflow integrated with an EMR. Known for data-driven UX decisions (A/B testing) and pragmatic modernization of critical systems (3DS2 upgrade) with measurable conversion and risk improvements.”
Junior Software Engineer specializing in Full-Stack and GenAI/LLM applications
“LLM/RAG practitioner building clinician-facing AI search and Q&A inside EHR workflows, focused on trust, latency, and safety (grounded answers with citations, PHI controls, encryption/audit logs). Demonstrated real-time incident response for production LLM systems (e.g., fixing a metadata-filter deployment regression to prevent irrelevant results/cross-patient leakage) and strong demo/enablement skills for mixed technical and clinical stakeholders; also shipped a multi-model RAG tool at OrbeX Labs with upload/search/audit features for day-to-day adoption.”
Junior Machine Learning Engineer specializing in computer vision and generative AI
“CoreAI intern at The Home Depot who improved the Magic Apron Assistant by building a production video ingestion + RAG retrieval system for long videos (uploads and YouTube), including a graph-based retrieval module to speed up and improve relevance. Experienced with Kubernetes orchestration (HPA) and production reliability practices like caching, monitoring, regression testing, and stakeholder-driven requirements.”
Mid-level AI/ML Engineer specializing in MLOps and cloud-deployed ML systems
“ML/AI engineer who built and productionized an NLP system at PurevisitX, orchestrating end-to-end ML workflows with Airflow (S3 ingestion through auto-retraining) and optimizing for drift and low-latency inference. Also partnered with Citibank risk teams on a fraud detection model, translating results via dashboards and iterating thresholds based on stakeholder feedback.”
Mid-level Software Engineer specializing in Java microservices and distributed systems
“Systems Engineer at Tata Consultancy Services with hands-on ownership of enterprise logistics microservices (Spring Boot) using Kafka integrated with Azure Event Hubs, including partitioning strategies and operational handling of consumer lag/duplicate events. Also built a full-stack road-accident blackspot detection application using Python-based spatial clustering and model evaluation with a JavaScript/Mapbox frontend.”
“Built an AI-based voice interviewer platform at 7C Lingo to automate early-stage candidate screening, owning the full lifecycle from architecture through deployment and weekly production iterations. Implemented a TypeScript/Next.js recruiter dashboard with a Flask/Postgres backend and AWS S3, plus modular services for transcription/analytics/session management using state-driven async workflows. Also created an internal Whisper-powered transcription and editing tool that evolved into a collaborative, versioned, live-transcription system.”
Mid-Level Software Engineer specializing in AWS cloud-native microservices
“Backend-focused engineer who owned an end-to-end Python/Flask service at Viasat powering a 1000+ user internal React app, including API design, Postgres performance tuning (~50% faster), Dockerization, and CI/CD. Demonstrated strong problem-solving by building custom EDN parsing logic and has built near real-time AWS SQS/Lambda pipelines with DLQs and autoscaling patterns; currently ramping on Kubernetes/GitOps (ArgoCD).”
Mid-level Software Engineer specializing in cloud-native microservices for FinTech and Insurance
“Backend engineer who owned an order management API built with Python/FastAPI and PostgreSQL, integrating payment and shipping providers with strong reliability patterns (idempotency, async workers, retries/backoff, circuit breakers). Experienced deploying services to Kubernetes using a GitOps model with ArgoCD (auto-sync, self-healing, pruning, rollbacks) and building high-volume Kafka streaming pipelines. Has also supported phased cloud-to-on-prem migrations with a focus on security monitoring/SIEM log continuity.”
Mid-Level Software Engineer specializing in AI automation and full-stack FinTech
“Built an AI-powered loan automation dashboard using React and open-source JavaScript libraries, with hands-on experience improving real-world performance by reducing re-renders and optimizing/caching multiple API calls. Also produced developer-friendly API documentation for a voice assistant project, helping teammates integrate features faster with fewer errors.”