Pre-screened and vetted.
Mid-Level Software Developer specializing in API development and test automation
“Self-taught frontend developer with React/TypeScript project experience and strong QA background. Contributed as a QA tester on a Skunkworks web app by refining large story tickets, defining happy-path/edge test cases, and setting sprint metrics; also improved a legacy PHP web app by modularizing SFTP bulk upload code and enhancing page navigation.”
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.”
Mid-level Full-Stack Engineer specializing in cloud-native DevOps and Kubernetes
“Full-stack engineer with strong production experience improving performance and reliability of data-heavy analytics products. Has shipped end-to-end features spanning Node/Express + PostgreSQL + Redis and React/TypeScript, deployed via Docker/GitHub Actions to AWS EKS with Helm, and monitored with Datadog/CloudWatch; also built a Python compliance automation backend for AWS security monitoring with RBAC, versioned REST APIs, and resilient throttling-aware processing.”
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.”
Intern Full-Stack Engineer specializing in AI-powered products
“Software engineer (internship experience) who built and owned an AWS serverless multi-user “challenge” feature end-to-end (UI + REST APIs + DynamoDB + deployment), delivering measurable gains in latency (-30%), debugging time (-50%), and join drop-offs (~-30%). Also productionized a multilingual RAG-based QA system with vector retrieval and guardrails, improving accuracy to ~85% and driving ~20% DAU growth.”
Mid-Level Full-Stack Software Engineer specializing in FinTech and cloud-native microservices
“Built and shipped a production LLM-powered incident response agent for a microservices platform, automating alert triage and safe remediation recommendations with strong guardrails (RAG grounding, structured JSON outputs, rule-based validation, and human-in-the-loop). Implemented state-machine orchestration (Redis/Kafka), comprehensive eval/monitoring, and an error categorization pipeline that cut hallucination errors ~40% and reduced MTTR ~30%.”
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.”
Mid-level Software Development Engineer specializing in Python, APIs, and AWS
“Backend engineer with experience modernizing legacy systems and building modular Python/Flask services, including a REST-to-GraphQL migration for an e-commerce platform that improved API response time by 45%. Strong in performance and scalability work across PostgreSQL/SQLAlchemy (indexing, JSONB, N+1 fixes, connection pooling) and high-throughput systems (Celery + Redis), plus integrating ML microservices with TorchServe, Kafka streaming, feature stores, and Prometheus/Grafana monitoring.”
Mid-level Full-Stack Software Engineer specializing in React, Node.js, and Android media SDKs
“Backend/data engineer who built an end-to-end real-time stock analytics platform: ingesting multi-source market data via Kafka/APIs, transforming it into dashboard metrics (e.g., Bollinger Bands), and storing in BigQuery/MySQL. Strong DevOps/GitOps experience deploying Python/Node microservices on Kubernetes with Docker/Helm, CI/CD (GitHub Actions/Jenkins), and ArgoCD, plus hands-on troubleshooting and migration work.”
Senior Full-Stack Developer specializing in Node.js/TypeScript, cloud, and data engineering
“Frontend/fullstack lead who inherited a messy psychological app with production issues, drove a rapid stabilization (2–3 weeks) and major performance/architecture overhaul (Redux Toolkit, memoization, caching, lazy loading, CDN offload to S3/CloudFront). Also owns delivery and infrastructure practices (multi-env, Docker, GitHub Actions CI/CD, AWS ECS + load balancing) and led a 1-week POC for an AI-powered trucking management system (app.neblo.ai).”
Senior Full-Stack Engineer specializing in modern web applications
“Full-stack developer with seven years of experience who has built production systems across AWS serverless infrastructure, Django applications, and user-facing web products in domains like emergency response, fintech/investing, recruiting, and conference management. Particularly notable for combining technical architecture with product thinking—e.g., modernizing a crash-tracking platform for emergency responders and materially improving trust-driven conversion in a trading-card fractionalization product.”
Senior AI Engineer specializing in machine learning, GenAI, and MLOps
“Built an end-to-end agentic population health strategy copilot for healthcare leadership, turning broad chronic disease questions into structured, evidence-backed strategy briefs. Stands out for combining healthcare domain knowledge with production-grade GenAI implementation, including LangGraph orchestration, Databricks/MLflow deployment, human review, and quality gates focused on citations, metrics, risks, and safety.”
Junior AI/ML Engineer specializing in LLMs, RAG, and cybersecurity
“AI/full-stack builder with hands-on experience shipping conversational and agentic products, including a travel itinerary assistant, a multi-agent data analysis platform, and a self-correcting RAG system. Also brings academic research depth from Syracuse University, where they helped develop tiny-LLM-based IoT threat mitigation and presented an accepted paper at FLAIRS 39.”
Senior Technical Lead and Full-Stack Engineer specializing in cloud, AI, and enterprise platforms
“Engineering leader and player-coach who says he joined Freeing Returns during a transition from sales-led services to SaaS, architected the platform from the ground up, and helped hire a 10+ person team across engineering, product, and delivery. He also describes leading an AI-based fraud detection system on Salesforce with data lake and pipeline architecture, combining startup build-from-scratch execution with hands-on technical leadership.”
Senior Go Engineer specializing in low-latency FinTech platforms
“Backend/distributed-systems engineer with 9 years of Go experience, focused on financial-services platforms where performance, reliability, and regulatory auditability are critical. He has built low-latency market data infrastructure (p99 under 8ms) and optimized compliance/reporting systems used by finance and audit teams, combining strong systems design with practical production operations.”
Junior Software Developer specializing in LLMs, RAG pipelines, and web applications
“Backend engineer (Encore) who led the evaluation and redesign of a high-volume, low-latency real-time retrieval/ranking and inference platform on AWS, shifting from tightly coupled services to a modular architecture for better fault isolation and independent scaling. Strong focus on production reliability, observability, and security (JWT/RBAC, multi-tenant scoping, Postgres/Supabase RLS), with disciplined migration playbooks (feature flags, shadow traffic, dual writes/reconciliation).”
Mid-Level Full-Stack Software Engineer specializing in mobile apps and payments
“Startup engineer who owned an end-to-end carpool marketplace experience at FavorIt (React Native, Firebase/Firestore, Cloud Functions, Stripe) and iterated rapidly using Mixpanel + feature flags while applying rigorous integrity controls for booking and payments. Also built a TypeScript/React + Go/Postgres workout tracker and previously worked on Spring Boot microservices for financial-institution workflow automation with event-driven patterns (outbox, idempotency, backpressure tuning).”
Junior Full-Stack Software Engineer specializing in FastAPI, Node.js, and React
“Frontend engineer in fintech who led a client onboarding platform end-to-end, building a scalable React/TypeScript architecture with Redux-driven multi-step verification workflows. Strong focus on quality at scale through UI automation/E2E testing and CI/CD (GitHub Actions + Docker), enabling faster releases (bi-weekly to daily) while staying stable despite evolving backend APIs.”
Mid-level Full-Stack Cloud Engineer specializing in GCP/Azure and AI-powered applications
“Backend/DevOps-leaning engineer who has owned a Python serverless platform on AWS (Lambda, DynamoDB, Step Functions), including complex multi-step business workflows with transaction-based consistency and robust failure handling. Also supported an on-prem SQL to Azure Data Lake migration by building and monitoring Python + Azure Data Factory ETL pipelines, and led GitOps-style CI/CD automation with GitHub Actions (tests, security scans, automated deployments).”
Junior Full-Stack Java Developer specializing in FinTech payments
“Full-stack engineer with hands-on experience building end-to-end applications using Java/Spring Boot and React, including Dockerized deployment and RabbitMQ-based messaging. Worked on a high-volume payment processing system at Alacriti, focusing on performance (query optimization, caching) and reliability with monitoring via AWS CloudWatch.”
Mid-level Full-Stack Software Engineer specializing in cloud-native apps and AI copilots
“Internship project building and deploying a LLaMA-based, RAG-enabled copilot inside a Professional Services Automation platform, enabling natural-language navigation, text-to-SQL reporting, and project/resource/budget insights across multiple modules. Addressed real production issues like context drift and vague queries with hybrid search, metadata enrichment, and an intent classification/rewriting layer, orchestrated via Apache Airflow—ultimately cutting PMO reporting time by 40%.”
Senior Full-Stack Engineer specializing in web, mobile, and cloud platforms
“Frontend engineer/lead who has shipped multiple production applications including VentureRamp (multi-platform crowdfunding app, deployed early 2024), DataPotter (large-scale stakeholder tracking dashboard), and Nasdmobile (OTC stock trading app). Emphasizes scalable microfrontend/modular architecture, strong state management (React + TypeScript + Redux Toolkit), and disciplined release practices (feature flags, phased rollouts, monitoring) while leading teams through sprints and knowledge-sharing.”
Senior Full-Stack & Mobile Engineer specializing in React and React Native
“Frontend engineer/team lead currently overseeing a 5-person team building an AI trading mobile application, using modular architecture and Jest-based testing to maintain quality as features scale. Also develops a trading/research platform in Next.js/React/TypeScript with Tailwind and Redux, including complex broker registration workflows and experience separating on-device AI components from core business logic.”
Junior Cloud & AI Infrastructure Engineer specializing in Agentic AI and AWS
“Built and deployed a production AI career-advice agent designed to combat unreliable/generic LLM guidance by grounding outputs in retrieval-first RAG over resumes/job/hiring data, with multi-step reasoning, structured memory, and evidence-only prompting to reduce hallucinations. Implemented the system with LangChain/Python and deployed on AWS as scalable microservices orchestrated via REST and asynchronous calls, iterating closely with career coaches and students.”