Pre-screened and vetted.
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.”
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.”
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 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 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.”
Mid-level Full-Stack AI Engineer specializing in deployed LLM agents and RAG systems
“Built a real-time AI meeting assistant using a Chrome extension that streams audio to a backend LLM workflow with transcription and RAG, then hardened it for production with queue-based streaming, async pipelines, security controls, and full observability. Also has hands-on startup sales experience, partnering with customers to define measurable technical win conditions (latency/accuracy) to close deals and drive adoption.”
“Forward Deployed Engineer at EasyBee AI who productionized a self-storage customer’s multi-agent LLM system end-to-end—rebuilding it with LangGraph/CrewAI, integrating with real property management + CRM systems via an MCP server, and adding observability/guardrails for reliable daily use. Experienced in live troubleshooting of agentic workflows, developer demos/workshops (including an open-source project, MerryQuery), and partnering with sales to close deals through customer-specific technical demos and fast integration feedback loops.”
Junior Full-Stack Software Engineer specializing in Python APIs, React, and cloud AI integrations
“Customer-facing software engineer who builds and deploys practical AI/RAG solutions (e.g., an AI assistant for searching billing PDFs) by deeply understanding support workflows and iterating with users. Demonstrates strong production instincts—quickly stabilizing peak-traffic API timeouts with caching/background jobs, then implementing durable fixes with proper monitoring and maintainable code practices.”
Junior AI/Full-Stack Software Engineer specializing in ad automation and LLM systems
“Full-stack engineer with deep ad-tech/marketing automation experience, building production tools that reduce programmatic ad waste and improve search ads performance. Shipped and operated AWS-deployed, Dockerized systems with Postgres/Redis and strong observability (Datadog/OpenTelemetry), and delivered measurable impact (25k campaigns processed, 50k sites negated, 3–4 hours/week saved). Built scalable abstractions for multi-platform ad integrations, enabling rapid onboarding of additional clients.”
Senior Full-Stack Software Engineer specializing in AI-powered web and mobile applications
“Backend/full-stack TypeScript engineer who has owned end-to-end, production-oriented systems including an AI property management platform (NestJS/Postgres/WebSockets on Google Cloud using Gemini Vision) and an AI logistics platform (Node/Redis queues/Postgres) focused on low-latency, correctness, and observability. Also designed a public GraphQL API and TypeScript SDK for education partners at StudyFetch, citing 40+ partner integrations in the first quarter.”
Senior Gameplay Programmer specializing in Unity systems and game development
“Gameplay engineer with hands-on ownership of core systems across both Unity/C# and UE5, including a full item/inventory/vendor pipeline and a server-authoritative co-op multiplayer architecture. Stands out for combining data-driven design, tooling, and disciplined validation workflows—including LLM-assisted content generation—to improve iteration speed and stability.”
Mid-level Full-Stack Software Engineer specializing in AI-enabled web apps and data platforms
“Software engineer who built an AI marketing/outreach agent end-to-end: Next.js (App Router + TypeScript) frontend integrated with a Python/Django REST backend using LLMs (Gemini, ChatGPT-4o) and SQL databases. Demonstrated measurable performance wins—improved a 100k-record UI by 15% (Lighthouse) and cut a Postgres-backed search API from ~3s to ~1ms via indexing—while also owning post-launch monitoring (webhooks/cron, New Relic/CloudWatch) and customer support.”
Junior Full-Stack Software Engineer specializing in mobile, cloud, and GenAI integration
“Software engineering intern with hands-on ownership of a Java/Spring Boot order management microservice, including production performance tuning via Redis caching and database indexing driven by API logs/metrics. Also contributed to a production mobile-backend LLM feature using RAG with embeddings over structured data and documents (DB + object storage), with guardrails to keep responses grounded.”
Entry-level Software Engineer specializing in full-stack and AI systems
“Software engineer with hands-on experience spanning backend APIs, streaming data systems, and cloud/infrastructure automation, who is already using agentic AI workflows in a disciplined way. Stands out for combining practical systems work in Spring Boot, Kafka/Spark/ClickHouse, and Terraform/Kubernetes with a thoughtful approach to AI oversight, architecture, and multi-agent orchestration.”
Senior Applied AI Engineer specializing in RAG and full-stack systems
“Backend engineer with experience building an end-to-end civic tech AI platform that ingests city council meeting videos, transcribes them with Whisper, and enables natural-language Q&A via a LangChain/FAISS RAG pipeline. Demonstrated strong systems thinking by tuning retrieval for accuracy/latency/memory (cutting response time ~3s→1s and memory ~500MB→25MB) and by safely migrating an ERP from monolith toward services using dual writes, reconciliation, and idempotency to protect financial workflows.”
Junior Full-Stack Java Developer specializing in Spring Boot microservices and cloud DevOps
“Software engineer with hands-on production experience deploying Spring Boot services to AWS using Docker and Jenkins CI/CD, focused on stable releases, easy rollback, and performance improvements through monitoring/logging and query optimization. Has proven cross-layer troubleshooting skills (identified packet loss causing intermittent timeouts via network traces) and experience collaborating on-site with operators in industrial/IoT-style environments, including working alongside robotics/PLC teams.”
Junior Full-Stack Software Engineer specializing in AI/ML platforms and microservices
“Graduate-school lab engineer who built and owned the final architecture of a Microservices Hub that integrates REST APIs, issues API keys, monitors 10+ Linux servers, and visualizes service dependencies via a topology graph. Strong in bridging legacy and modern stacks (Dockerized and non-Dockerized services like Apache/screen) using deep Linux/networking knowledge, plus practical real-time audio streaming for STT/TTS and experience mentoring others.”
Junior Solutions Engineer specializing in full-stack automation and LLM prompt engineering
“Built and productionized an LLM-powered customer support system using a RAG architecture with structured document ingestion, embedding retrieval, and prompt templates for product-specific grounding. Experienced diagnosing live agent/workflow failures (e.g., retrieval regressions after new docs) by refactoring ingestion/chunking and adding grounding constraints plus evaluation benchmarks. Also supports go-to-market by joining discovery calls, shaping MVP workflows into demos/prototypes, and creating post-launch documentation to drive adoption.”
Mid-level Full-Stack Product Engineer specializing in React, TypeScript, and UX
“Full-stack engineer focused on Next.js (App Router) and TypeScript who has shipped and owned production role-based dashboards end-to-end, including post-launch reliability/performance work. Demonstrated measurable UI performance improvements (35–40% faster initial load) and strong backend rigor with Postgres query/index optimization (300ms to 30ms) plus durable Temporal-orchestrated onboarding/data-sync workflows with idempotency and retry strategy.”
Senior Software Engineer / Technical Lead specializing in cloud-native microservices
“LLM/agentic-systems practitioner who shipped a recruiting resume-assistant from prototype to production, tackling hallucinations and multi-format document ingestion (PDF/images with OCR). Strong in real-time workflow debugging (logs/traces, reproducing prod issues) and pragmatic mitigation (feature flags), and helped drive customer adoption by presenting impact data and creating educational materials.”
Intern Full-Stack Engineer specializing in Java, React, and cloud-native backend systems
“Frontend-focused engineer with startup experience (SmartPath, OPC AI) who owned and evolved an internal React/TypeScript component library treated like OSS—refactoring core form and API wrapper modules for stability, type safety, and smaller bundles. Comfortable diagnosing production issues via logs/API traces and shipping end-to-end fixes with tests and documentation, including internal workshops to drive adoption.”
Junior Data Analyst specializing in analytics, BI, and machine learning
“Analytics professional with experience spanning infrastructure, energy, and digital engagement data. They have built SQL and Python workflows to turn messy operational data into trusted reporting assets, and led a wind turbine SCADA analysis that quantified roughly $1M in cumulative performance loss and translated findings into actionable Power BI dashboards.”