Pre-screened and vetted.
Entry-level product and project management candidate specializing in operations and user insights
“Early-career candidate with a blend of product research and project coordination experience from a BeReal Product Innovation Externship and Aspire Skill Development internship. They bring strong analytical and organizational skills, including user interviews, competitive benchmarking, prototyping, and stakeholder tracking, with a demonstrated contribution to reducing missed deadlines by 20%.”
Mid-level Full-Stack Software Engineer specializing in SaaS and AI-enabled web applications
“Full-stack engineer who led an end-to-end rebuild of a service-agent case management app (React SPA + backend/DB updates) and added Datadog monitoring, improving agent throughput by ~1 case/hour and saving roughly $15K/month. Experienced in incremental legacy modernization (including moving a legacy React frontend toward a Rails-based approach) with heavy unit/E2E testing and strong cross-team stakeholder communication.”
Staff Frontend Engineer specializing in React platforms and SaaS architecture
“Frontend engineer who owned a globally deployed, multi-brand appointment-booking experience for Estée Lauder, balancing React modernization with legacy platform constraints. Stands out for combining micro-frontend architecture, browser-performance optimization, and product analytics tools like Fullstory, NPS, and attribution tagging to drive both UX improvements and measurable revenue impact.”
Mid-level Full-Stack Engineer specializing in cloud-native Java and AI platforms
“Full-stack engineer with strong cloud and platform experience spanning React, Go, AWS, Kafka, and Terraform. Has led complex migrations from monolithic/containerized systems to microservices and cloud deployments, built compliance-oriented logging infrastructure, and improved a broken frontend codebase to achieve a 3x performance gain while making it easier for other developers to extend.”
Mid-level Full-Stack Java Developer specializing in retail, banking, and healthcare systems
“Full-stack engineer with hands-on ownership of a real-time retail inventory and shipment tracking platform, spanning React/Angular dashboards through Spring Boot microservices, PostgreSQL, and Kafka. Stands out for building operationally impactful systems in ambiguous environments and for thinking carefully about scalability, monitoring, and user-friendly workflow automation, even without direct production AI experience.”
Mid-level Full-Stack Engineer specializing in AI and cloud platforms
“Built end-to-end product features spanning full-stack web development and LLM-powered systems in an early-stage startup environment. Notably shipped an AI financial assistant chatbot with agent routing, validation, fallback handling, and production monitoring, and also owned a scheduling system integrating Next.js, backend APIs, database design, and Google Calendar OAuth.”
Mid-level Full-Stack AI Engineer specializing in LLM agents and RAG systems
“AI product engineer with hands-on experience shipping enterprise LLM systems at General Motors, including NL2SQL analytics, RAG-based enterprise search, and multi-agent document analysis. Stands out for combining strong technical depth in LangChain/Vertex AI/Pinecone/Redshift with disciplined evals, human-in-the-loop design, and clear business impact such as 70% to 90%+ accuracy gains, 3x analyst throughput, and rapid MVP delivery in 6 weeks.”
Mid-level Full-Stack Engineer specializing in enterprise platforms and distributed systems
“Front-end/product engineer who has built an AI-assisted browser discussion platform combining vector-search-backed LLM responses with real-time chat, plus high-scale analytics interfaces for business users. Stands out for blending modern UI engineering with browser internals knowledge, including cross-browser extension behavior and tricky iOS Safari viewport/rendering issues.”
Mid-level Software Engineer specializing in backend web applications and APIs
“Backend-leaning full-stack engineer who has shipped both a SaaS analytics/A-B testing platform and an AI-driven fraud monitoring product in production. Stands out for combining React/TypeScript frontend work with Python/Java backend systems, event-driven architecture, and practical LLM integration grounded by validation and human analyst feedback, with measurable impact on engagement, performance, fraud accuracy, and false positives.”
Junior AI software engineer specializing in agentic workflows and cloud platforms
“AI/full-stack builder who has owned end-to-end LLM features in both creative tooling and education workflows. Built a multi-agent film-production workspace for Backlot and an automated ingestion pipeline at iOffer.AI that cut counselor manual entry by 70%, with hands-on depth in orchestration, validation, monitoring, and human-in-the-loop system design.”
Mid-level Software Engineer specializing in mobile app development for healthcare
“Frontend engineer working on United Healthcare's rewards experience across mobile and web, with experience building high-visibility user financial history features for millions of users. They emphasize maintainable React/TypeScript architecture, UI correctness, and production troubleshooting with Datadog RUM, and also described a custom CMS-driven rendering framework in Next.js.”
Senior Full-Stack Developer specializing in JavaScript, cloud, and AI-powered web apps
“Full-stack engineer with 8 years of experience spanning regulated healthcare IoT and enterprise security SaaS. Has worked on a high-growth healthcare equipment platform and DigiCert's certificate lifecycle management product, combining hands-on React/Node.js development with compliance, auditability, and reliability requirements. Currently seeking a more code-heavy role after moving into a more advisory position.”
Mid-level Software Engineer specializing in full-stack web and AI applications
“Software engineer who owned an Order Management System end-to-end at Reliance Jio, improving large-table performance via UI virtualization shipped behind feature flags and refined through direct ops-user observation. Also built an OCR automation tool at Piramal Realty using Python/Tesseract with validation and manual correction fallbacks, driving adoption by operations teams. Experienced integrating with Kafka-based microservices and improving observability using structured logging and correlation IDs.”
Junior AI Engineer specializing in LLM systems and applied machine learning
“Yogesh is an AI/full-stack engineer from LangChain who says he was the sole developer and core maintainer of OpenSWE/OpenSpeed, an asynchronous coding agent in LangSmith Cloud that turns requests from Slack, Linear, and GitHub into reviewable PRs. He emphasizes production-grade agent infrastructure: event-driven workflow design, typed run states, observability, retries, and latency improvements via pre-warmed sandboxes.”
Mid-level Full-Stack Developer specializing in React, Spring Boot, and microservices
“Backend engineer with experience at KPMG evolving an audit/reporting platform from monolithic components to microservices (Spring Boot/Node.js), improving API performance and enabling independent deployments. Demonstrates strong production focus across secure API design (FastAPI, JWT/OAuth2, RBAC/RLS), incremental migrations with feature flags, and robustness improvements like optimistic locking to prevent race conditions.”
Mid-Level Full-Stack/Backend Engineer specializing in AWS, APIs, and GenAI systems
“Backend engineer who built the core backend for Air Kitchens’ discovery/booking platform on AWS (Node + Python, DynamoDB, SQS/Lambda), optimizing for fast user-facing APIs and scalable async workflows. Introduced an AI matching service with a deterministic pre-filter + LLM ranking approach to balance latency vs quality, and has hands-on experience with production security (JWT/RBAC/RLS), CI/CD, and blue-green, staged migrations from Django to modular services.”
Mid-level Software Engineer specializing in backend, cloud-native microservices, and LLM apps
“LLM/agentic systems practitioner who repeatedly takes customer-facing LLM prototypes into production by operationalizing prompts, hardening RAG pipelines, and adding monitoring/guardrails. Has hands-on experience debugging intermittent production failures under high traffic (vector store timeouts/empty retrieval) and implementing fail-safe behavior plus alerting. Also partners closely with sales in pilots/POCs, customizing demos with customer data and running side-by-side comparisons to drive adoption.”
Mid-level Full-Stack Developer specializing in web, mobile, and IPTV applications
“Frontend engineer with hands-on experience revamping IPTV native TV apps (Android TV, Xfinity, LG, Samsung), building scalable, lazy-loaded home page and content experiences that remain stable as backend playlists change. Emphasizes component/modular architecture (including MVP on Android TV), strong quality practices (CI, unit tests, code reviews, manual device testing), and modern React+TypeScript state management using Zustand with clean separation of business logic from UI.”
Mid-level Java Full-Stack Developer specializing in banking and e-commerce microservices
“Software engineer/product-focused builder who delivered real-time supply chain inventory dashboards to replace a legacy system, integrating directly with ERP/WMS/TMS to eliminate manual reporting. Uses TypeScript/React with Redux Toolkit on the frontend and microservices + REST APIs on the backend, with performance improvements via Redis caching and a strong focus on user-feedback-driven prioritization and observability in distributed systems.”
Mid-level Full-Stack Developer specializing in cloud-native microservices and IoT platforms
“Full Stack Developer (recently at Cisco Systems) building end-to-end web applications with Angular frontends and Spring Boot microservices backed by MySQL/JPA, including JWT + role-based access. Has hands-on experience with high-volume, real-time data processing/visualization and has solved complex UI state consistency issues using RxJS BehaviorSubjects; also applies layered state patterns in React with Redux Toolkit and uses AI dev tools (Cursor/Claude) strategically.”
Mid-Level Full-Stack Java Engineer specializing in microservices and cloud platforms
“Frontend/platform-leaning engineer who owned a shared React component library (design-system style) adopted across multiple SPAs, with strong discipline around SemVer, deprecation strategy, and developer documentation. Also has backend/distributed-systems experience diagnosing and fixing a Kafka microservice race condition and has led prioritization/migration planning in an unstructured monolith-to-microservices environment (Centene).”
Mid-Level .NET Full-Stack Developer specializing in banking and cloud-native microservices
“Full Stack Engineer with hands-on experience owning customer-facing products end-to-end, emphasizing fast iteration via feature flags and risk-based testing for critical user flows. Built TypeScript/React systems with shared types and clean backend layering, and has microservices experience using RabbitMQ to decouple services and manage scale issues like queue backlogs. Also created an internal dashboard for dev/QA to centralize build/test/deploy visibility and iterated on it through lightweight user research and usage metrics.”
Mid-level Full-Stack Software Engineer specializing in cloud-native microservices
“Full-stack engineer who owned end-to-end delivery of a customer-facing financial services web platform and built internal tooling for engineering teams. Strong in microservices and event-driven systems (Kafka/RabbitMQ), distributed transaction management (saga), and production performance/observability—achieving ~40% backend response-time improvement through database and query optimization.”
Junior Data Scientist/Data Engineer specializing in ML pipelines and analytics
“Machine Learning Intern at Docsumo who delivered a customer-facing fraud-detection solution end-to-end: rebuilt the pipeline, deployed a Random Forest model, and shipped a Python/Flask microservice on AWS SageMaker. Drove measurable production impact (precision +30%, processing time cut in half, manual review -60%, customer satisfaction +15%) and demonstrated strong customer integration and live-incident response skills.”