Pre-screened and vetted.
Mid-level Full-Stack Java Engineer specializing in Generative AI and cloud microservices
“Full-stack engineer who has delivered production customer analytics/dashboard features using Next.js App Router + TypeScript on the frontend and Java Spring Boot microservices on the backend. Demonstrates strong production ownership (monitoring latency/error rates/adoption) plus hands-on performance work across React rendering and Postgres query/index optimization, and has implemented Temporal-like durable workflows with retries and idempotency.”
Mid-level AI Engineer specializing in RAG, conversational AI, and agentic systems
“Built and deployed a production RAG-based clinical decision support assistant at MedLib, focused on fast, trustworthy answers from large medical documents. Demonstrates deep practical experience improving retrieval accuracy (semantic chunking + metadata-aware search), controlling hallucinations with grounded generation and thresholds, and adding clinician-requested citations using chunk metadata, with evaluation driven by healthcare professional review.”
Mid-level Software Engineer specializing in cloud-native backend and distributed systems
“Backend/full-stack engineer with experience building customer-facing contact-center automation (agent assignment) and internal editorial/data operations APIs for life-sciences ontology management. Strong in microservices and event-driven systems (Spring Boot + Kafka), third-party integrations (Genesys/Five9), and pragmatic iteration via MVP scoping, tight stakeholder demos, and observability-focused reliability.”
Mid-Level Software Engineer specializing in backend systems, cloud, and applied LLM/NLP
“Applied LLMs to classify long nonprofit mission statements into 8 segments without labeled data, using an ensemble of clustering/embedding methods plus zero-shot RoBERTa/BART and a Tree-of-Thought prompting pipeline with LLM-as-judge evaluation (Gemma). Also built LangChain/LlamaIndex agentic RAG workflows including a text-to-SQL data analysis assistant grounded on DB schema with retries and performance optimizations on an HPC cluster.”
Senior Full-Stack Engineer specializing in MERN, AWS, and scalable SaaS platforms
“Frontend lead for B2B SaaS products, owning React + TypeScript architecture end-to-end and scaling complex dashboards/workflows with a feature-based structure, shared design system (Tailwind), and strong quality automation. Experienced shipping high-impact features quickly using incremental delivery, feature-flagged rollouts, and performance profiling/optimization to keep production stable as usage grows.”
Senior Software Engineer specializing in Node.js/NestJS and FinTech platforms
“Frontend engineer who led end-to-end development of the Neelum transportation admin panel (React + TypeScript + AntD), building scalable dashboards and multi-step workflows for users/roles/bookings/operational zones. Emphasizes maintainable feature-based architecture, typed API contracts, performance optimization for data-heavy UIs, and disciplined quality/rollout practices (regression checks, feature flags) in fast-paced environments.”
Executive Technology Leader specializing in distributed systems and multi-cloud infrastructure
“Early-stage builder who blends deep technical product work with go-to-market execution: created developer-focused platform tooling (Rust/Node/React) and at Harper moved from customer success into sales/partnerships, leading an Akamai partnership that ultimately helped close Walmart. Currently building a distributed application platform in Rust and iterating on macro-based abstractions to make Rust feel as approachable as Node.js; has not yet closed a seed round and is seeking a trusted operator counterpart.”
Junior Software Engineer specializing in full-stack web and AWS cloud automation
“Software developer with experience delivering and deploying customer-facing web applications, including an investment-focused platform requiring PostgreSQL/SQL optimization and hierarchical (adjacency list) data modeling. Has integrated payment APIs for a retail/antique shop use case, factoring in rate limits and documentation-driven implementation, and has handled time-sensitive production bugs via rapid replication and hotfix deployment.”
Junior Backend Engineer specializing in data platforms and cloud APIs
“Backend lead at a stealth startup and builder of MailIQ/MailBox—an automated Gmail inbox digest + cleanup system. Designed secure multi-account email ingestion and cost-efficient LLM-based summarization, and implemented robust unsubscribe automation using Playwright + OpenAI webpage analysis (including captcha-handling) with strong safety guardrails, incremental rollouts, and rollback strategies.”
Junior AI Data Engineer specializing in Azure Databricks lakehouse and GenAI RAG systems
“Backend/applied AI engineer from Cloud Rack Systems who built production GenAI/RAG and data platforms on Azure/Databricks at enterprise scale (2.5M records/day). Known for making LLM systems behave like deterministic services via strict retrieval contracts, citation-based validation, and strong observability—shipping a knowledge assistant used daily by 50+ users while driving hallucinations near zero and materially improving latency and cost.”
Mid-Level Full-Stack Engineer specializing in real-time systems and FinTech
“Backend engineer with hands-on experience modernizing a real-time logistics/tracking platform from a tightly coupled polling architecture to a service-oriented/microservices design using Node.js and WebSockets. Emphasizes contract-first FastAPI development, defense-in-depth security (JWT/OAuth, RLS/Supabase), and safe incremental migrations with feature flags and strong observability, delivering sub-second updates and improved performance under peak load.”
Senior Frontend Developer specializing in React, accessibility, and enterprise web apps
“Frontend engineer who has led end-to-end React + TypeScript initiatives, including a shared frontend module used across product lines/regions and an inventory discovery experience for large datasets. Strong in scalable architecture (feature-based, configuration-driven, role-aware components), design systems with Storybook, and performance/quality practices (profiling, CI/CD, automated testing, feature-flagged rollouts). Reported ~30% reduction in duplicate code after refactoring an existing React codebase.”
Junior Full-Stack Software Engineer specializing in web platforms and cloud-based systems
“Full-stack engineer with hands-on document extraction experience: built an end-to-end handwritten OCR pipeline using OpenCV + EasyOCR with spellcheck post-processing and a Tkinter-based manual correction workflow. Also brings practical distributed-systems and e-commerce reliability experience (REST orchestration, retries, logging, Stripe idempotency), and is candid about not yet shipping LLM agents to production.”
Junior Software Engineer specializing in backend systems and machine learning
“Independent builder of production-grade systems: shipped an end-to-end URL shortener with JWT auth, Redis rate limiting/caching, Postgres, Docker, and real-time analytics, and separately architected a Redis-backed distributed task queue handling 1000+ tasks/min. Demonstrates strong distributed-systems instincts (atomicity, retries/DLQ, idempotency, heartbeats) plus a focus on maintainable code and self-documenting APIs (FastAPI/OpenAPI, versioned routes).”
Mid-level Software Engineer specializing in backend systems and AI-powered platforms
“Backend engineer who built a production retrieval-augmented narrative analysis platform for 100-page screenplays using a Node/Express orchestrator and a Python/FastAPI AI engine, including a key redesign from disk-based uploads to in-memory streaming to eliminate Windows file-lock failures. Also led a refactor of a municipal vehicle tracking system into a C-based distributed engine handling 4M+ daily packets with 99.99% data integrity and automation that reduced manual ops by 50%.”
Mid-level AI Engineer specializing in Python, LLMs, and production ML systems
“Production-focused ML/AI engineer with hands-on ownership across classical ML and GenAI systems, from CV/NLP services to enterprise RAG. Stands out for combining research-to-production execution with measurable business impact: 40% processing-efficiency gains, 35% fewer support tickets, 5x latency improvement, and 3x throughput gains while maintaining safety and quality.”
Junior AI/ML Engineer specializing in AI agents and reinforcement learning
“Backend/AI engineer who built Matchable, an end-to-end AI-powered workforce matching platform using FastAPI, transformer-based NLP, PostgreSQL, and AWS, with a strong focus on practical system design tradeoffs. Also brings research-oriented experience from Los Alamos/ASU simulation work and has built multi-agent LLM workflows with schema validation and auditability, suggesting a thoughtful approach to reliability in AI systems.”
Intern full-stack software developer specializing in web and biomedical applications
“Built Python-based data workflow integrations for a Huntsman Cancer Institute research project, focusing on reliable upload, validation, processing, and retrieval of messy research data. Demonstrates strong practical instincts around automation hardening, observability, and translating ambiguous manual processes into structured workflows, including Selenium automation when APIs were unavailable.”
Mid-level Full-Stack Engineer specializing in scalable web and mobile applications
“Frontend-leaning full-stack engineer who discusses building production React features integrated with backend APIs, Redux, and Algolia search. Shows strong awareness of maintainability and release safety through TypeScript modeling, feature flags, Sidekiq for async processing, and post-launch monitoring of traffic and pod memory.”
Entry-level Full-Stack Engineer specializing in web, mobile, and AI-integrated applications
“Frontend-leaning full-stack engineer who has rebuilt a high-volume order management system in Next.js/TypeScript for 6000+ active orders and also owned end-to-end product/data architecture in Firebase/Firestore. Stands out for strong performance instincts, type-safe frontend architecture, and pragmatic 0→1 execution across UI, APIs, and data pipelines.”
Mid-level Full-Stack Software Engineer specializing in Java microservices and cloud platforms
“Full-stack engineer with strong React/TypeScript and Spring Boot experience in banking and financial systems, focused on real-time transaction monitoring and payment tracking products. Stands out for scaling high-volume dashboards, solving rendering bottlenecks in live data UIs, and owning features end-to-end from frontend through APIs, Oracle data layer, cloud deployment, and production monitoring.”
Entry-level Full-Stack Software Developer specializing in React, backend systems, and AI apps
“Full-stack engineer who has independently owned and shipped educational web products from concept through launch, including an AI-powered thermodynamics tutoring app and a physics learning platform tied to research publication. Strong in React plus AWS serverless architecture, with a clear pattern of working directly with non-technical stakeholders, iterating from user feedback, and maintaining production systems end-to-end.”
Senior Full-Stack Engineer specializing in cloud-native AI and Healthcare IT
“Built AIO, a 7-agent system that automatically fixes failed GitLab CI/CD pipelines in under 60 seconds using Redis queues, typed TypeScript contracts, and strong observability. Heavy AI user who still applies rigorous human review for logic, security, scalability, and code quality, and has made deliberate architectural choices rather than relying blindly on frameworks.”
Intern Full-Stack Software Engineer specializing in AI and SaaS platforms
“Built Syntriq, an AI-assisted deviation investigation platform for pharmaceutical manufacturers, owning the full stack from a 13-stage Python/FastAPI AI pipeline to a React report editor with source traceability. Stands out for combining strong technical execution with deep user discovery in a highly regulated FDA-sensitive domain, and for making pragmatic product decisions based on real QA investigator workflows.”