Pre-screened and vetted.
Senior Software Engineering Lead specializing in full-stack web applications and cloud platforms
“Frontend engineer with hands-on experience leading architecture and quality practices for React/Angular apps, including design system selection, code review/branching workflows, and Jest-based unit testing with a 100% coverage target. Built a React + TypeScript financial tool using Zustand/React-Redux, improved performance via lazy loading, and implemented input-sanitization utilities. Has managed fast-paced releases with Rally-based defect tracking and resolved a production deployment issue via rollback and YAML configuration fixes.”
Junior Software Engineer specializing in distributed systems and AI automation
“Backend engineer/technical lead with experience building and operating real-time blockchain analytics systems at Merkle Science. Owned high-traffic Django/DRF services and Kafka streaming pipelines processing millions of events daily, with deep focus on performance (N+1 fixes, indexing, caching) and reliability (DLQs, retries, monitoring). Also led containerization and Kubernetes/GitOps-style CI/CD on Google Cloud, including a migration off Google App Engine to reduce cost and improve scalability.”
Senior Full-Stack Software Engineer specializing in API architecture and AI agentic RAG systems
“Hands-on backend/AI engineer who solo-built two production Claude-based agent systems: an internal Slack RAG over Confluence/Jira/code/regulatory docs and a HIPAA/GDPR-compliant patient chatbot with embedding guardrails and expert-in-the-loop evals. Also architected a multi-region patient portal + microservices platform with Terraform/CI-CD and federated gateways, delivering major onboarding automation and strong reliability wins (PgBouncer, chaos/perf testing).”
Junior Software Engineer specializing in full-stack systems and LLM automation
“Full-stack engineer who shipped a production "Financial Insight" assistant dashboard in Next.js App Router/TypeScript, integrating a RAG pipeline (embeddings + ChromaDB + LLM) via route handlers and owning post-launch performance (latency, token cost, retrieval relevance). Also built/optimized Postgres-backed workflows for an outbound dialer and callback routing engine handling ~10,000 daily contacts, validating query performance with EXPLAIN (ANALYZE, BUFFERS).”
Mid-level Backend Software Developer specializing in cloud-native microservices
“Backend engineer with American Express experience maintaining an internal Python/Flask rewards simulation microservice used by product analysts and QA. Demonstrated strong performance and scalability work: moved batch simulations to Celery, added Redis caching to cut DynamoDB latency, and tuned Postgres/SQLAlchemy queries with EXPLAIN ANALYZE and composite indexes (bringing API responses under ~200ms by queueing jobs). Also has experience integrating ML via Flask-based model-serving APIs (scikit-learn/LightGBM packaged with joblib) and designing multi-tenant data isolation and tenant-specific configuration systems.”
Junior Software Engineer specializing in backend systems and LLM/RAG applications
“Full-stack engineer who built a cloud storage app feature (file upload/management) with Next.js App Router + TypeScript and owned post-launch improvements. Also has internship experience building a geospatial AI chatbot: designed Postgres/PostGIS data models and optimized spatial queries, and implemented an LLM workflow orchestrated with LangChain/LangGraph plus a RAG pipeline grounded in OpenStreetMap data to reduce hallucinations.”
Mid-level Backend Python Engineer specializing in APIs, microservices, and data pipelines
“Backend engineer (Marsh McLennan) who evolved a high-volume claims automation pipeline in Python, emphasizing thin APIs with background job processing, strong validation/retries, and production-grade observability. Experienced in secure FastAPI API design (centralized JWT/RBAC), multi-tenant Postgres/Supabase-style row-level security, and low-risk refactors using parallel runs and feature flags; targeting founding-engineer scope roles.”
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices
“Backend engineer focused on cloud analytics/cost-optimization systems, with strong AWS-centric architecture experience (serverless Lambda, ECS, CloudWatch). Demonstrated deep PostgreSQL/SQLAlchemy optimization at million-record scale (including JSONB/GIN indexing) and built production ML inference services with S3-based model versioning and Airflow retraining pipelines. Also has hands-on multi-tenant SaaS design (separate schemas + RLS) and high-throughput background processing using Celery/Redis with measurable performance gains.”
Mid-level Backend Software Engineer specializing in cloud-native distributed systems (Healthcare IT)
“Data engineer with healthcare domain experience who has owned end-to-end pipelines and APIs at UnitedHealth Group, processing ~8M records per batch. Strong focus on data quality (multi-layer validation), reliability (monitoring/logging, retries/idempotency), and performance (Spark/SQL tuning, caching), with experience standing up early-stage systems using Python, Docker, and CI/CD.”
Staff Front-End Engineer specializing in high-performance web apps and AI products
“Frontend engineer who built uichallenges.design end-to-end in Next.js, delivering hourly AI-generated challenges across timezones and a CDN-backed gallery of 1k+ items while staying fast for 100s of weekly active users. Also led a full replacement of Zenhub’s kanban board, forking DnD tooling and adding custom virtualization + Redux to support thousands of items with real-time socket updates, shipped safely via gradual rollout with Sentry/Mixpanel and A/B testing.”
Mid-level Full-Stack & AI Engineer specializing in cloud, data platforms, and LLM automation
“Software engineer/product builder who has owned an agentic affiliate lead-gen platform end-to-end (Django + React/TypeScript) and deployed it on Kubernetes in anticipation of 10x user growth from ~5K DAUs. Also has healthcare claims microservices experience using Kafka, including hands-on performance tuning to address consumer lag and broker pressure, and built an internal downtime alerting tool adopted across the organization.”
Mid-Level Software Engineer specializing in cloud-native microservices on AWS
“Backend engineer with experience across healthcare and fintech platforms (Anthem, Citia) building high-throughput Python microservices with strong compliance/security focus (HIPAA, tenant isolation). Has integrated ML workflows into production systems (ResNet embedding-based image similarity) using async pipelines (Celery/Redis) and AWS (Lambda/S3/ECS), delivering measurable performance and fraud/content-integrity improvements at scale.”
Mid-Level Software Engineer specializing in iOS and full-stack development
“Cross-platform (web + mobile) product engineer working on coupon clipping experiences. Built and shipped category-based filtering informed by external market data (Rakuten/Honey) and internal user-journey analytics, validated via A/B testing and resulting in a 30% traffic lift. Experienced handling on-call production incidents, including rapid root-cause analysis and hotfixing a mobile crash that was blocking a release.”
Mid-level Full-Stack Software Engineer specializing in FinTech and cloud-native microservices
“Backend engineer at Discover who built and scaled Python/Flask services for a card dispute resolution platform, tackling long-running external network validations with Celery+Redis and delivering measurable gains (response time ~3s to <300ms; throughput +40%). Experienced in high-scale PostgreSQL/SQLAlchemy optimization (partitioning, read replicas, N+1 avoidance), event-driven systems with Kafka, and integrating ML fraud detection using AWS SageMaker/Lambda/ECS with clear separation of real-time vs batch processing.”
Mid-level QA/SDET Automation Tester specializing in UI, API, mobile, and cloud testing
“SDET focused on end-to-end quality for web applications, owning UI/API/regression automation from framework design through CI/CD integration. Notably prevented a production payment/checkout incident by adding API validations that caught incorrect tax calculations (rounding logic) during CI before release, and has a track record of stabilizing flaky Cypress tests via robust selector and wait strategies.”
Senior Software Engineer specializing in cloud-native microservices and secure enterprise platforms
“Full-stack engineer with strong production ownership in banking/identity & entitlements systems, building Spring Boot + Postgres/Redis services and React dashboards, then deploying on AWS EKS with Jenkins CI/CD. Demonstrated impact through reduced authorization latency and fewer access-related support tickets, plus strong observability and reliability practices (CloudWatch, tracing, autoscaling, Kafka pipelines with DLQs and reconciliation).”
Executive CTO and product engineering leader specializing in AI-first SaaS platforms
“Multi-time founding team member who helped raise capital at HotSchedules and Axial Shift, contributing investor-facing narratives around cost to serve, technology vision, scalability, and market opportunity. Motivated by building companies from the ground up, they bring a hands-on zero-to-one mindset paired with a strong understanding of what angels and VCs need to see in a scalable, standards-compliant product.”
Mid-level Backend Engineer specializing in distributed systems and FinTech
“Engineer who uses AI and multi-agent workflows as a force multiplier while keeping architecture, security, scalability, and production quality under human control. Shared a concrete example of accelerating a backend-heavy SaaS email ingestion platform with authentication, role-based APIs, database models, and deployment setup using agent-style development and review.”
Junior Full-Stack Software Engineer specializing in backend systems and FinTech
“Built an AI-powered document extraction system at Copart that moved from initial POC to rollout across multiple yards, with customer-driven iteration including batch processing. Has hands-on full-stack experience spanning Java/Spring Boot backends, React frontends, and LLM-based workflows, with attention to reliability through multi-LLM fallback, retries, and post-processing.”
Entry-level Software Engineer specializing in distributed systems and AI
“Frontend-leaning full-stack engineer who has built operational dashboards in both startup logistics and distributed systems observability contexts. They helped ship Quickflora's delivery management platform used across multiple stores for thousands of daily deliveries, and also owned a metrics dashboard in ResLens handling node-level runtime data and 10k+ datapoints.”
Senior Software Engineer specializing in microservices and FinTech/e-commerce platforms
“Full-stack engineer with end-to-end ownership of a production customer plan activation and account management flow at T-Mobile, spanning Java/Spring Boot APIs, React frontend, and Docker-based CI/CD deployments. Demonstrated performance/scalability work (query optimization, indexing, caching) and measured success via improved retrieval speed and reduced support tickets.”
Senior Frontend Engineer specializing in React and FinTech SaaS
“Senior engineer at BDI Plus who is already using AI coding tools as a core part of daily development, with hands-on experience building enterprise LLM products such as ChatCDP AI for Morgan Stanley analysts. Particularly strong at making AI systems trustworthy and usable through auditable outputs, streaming UX, and resilient state-machine-driven error handling.”
Mid-level Full-Stack Developer specializing in FinTech and enterprise platforms
“Engineer with a pragmatic, production-focused approach to AI-assisted development, using tools like Copilot and ChatGPT to accelerate coding while maintaining strict validation for correctness, security, and performance. Particularly notable for building a multi-agent incident-resolution workflow for a financial platform, with specialized agents for log analysis, root cause identification, fix suggestions, and test generation.”
“Engineer with hands-on experience building and deploying end-to-end ML inference pipelines using SageMaker, TensorFlow, Scikit-learn, and Kafka-backed real-time data systems. Brings a strong distributed-systems mindset and has already operated in a tech lead capacity through architecture decisions, code reviews, and cross-functional coordination. Especially compelling for teams building production AI/ML platforms that need both practical execution and sound engineering judgment.”