Pre-screened and vetted.
Staff Full-Stack Software Engineer specializing in cloud-native microservices
Mid-Level Software Engineer specializing in backend microservices and cloud automation
Junior Software Engineer specializing in SaaS analytics and reporting
Executive IT leader specializing in digital transformation and enterprise systems
Senior XR Developer specializing in augmented reality for public safety
Mid-level Full-Stack Developer specializing in cloud-native FinTech and Healthcare IT
Mid-level Software Engineer specializing in financial dashboards and internal tools
Mid-level Front End Software Engineer specializing in React and TypeScript dashboards
Senior Technical Project Manager specializing in e-commerce and digital marketing
Director-level Technology Architect specializing in GTM systems, data, and AI
“Bootstrapped founder of ByteThirst, a launched browser extension and CLI that monitors and estimates the environmental cost of LLM usage. They are targeting a niche climate-tech/AI space with support for 14 platforms, a freemium subscription model, and a first-mover thesis backed by market research, market sizing, and profit projections.”
Mid-level Software Engineer specializing in cloud-native platforms and healthcare systems
“Backend engineer with healthcare-domain experience building a security-critical RBAC identity/authentication/authorization microservice suite used across hospital imaging platforms (X-Ray, Ultrasound, etc.). Demonstrates strong security mindset (mTLS, cert hygiene, JWT, pen-testing collaboration) and pragmatic scaling/reliability practices (Nginx load balancing, Redis caching, automated tests, canary rollouts).”
Mid-level AI/ML Engineer specializing in LLM applications and cloud-native systems
“LLM engineer who has shipped production AI systems, including an RFP requirements extraction platform (OpenAI o4-mini + Azure AI Search + FastAPI) achieving 90%+ accuracy and ~5x throughput through grounding, structured outputs, parallelization, and caching. Also partnered with legal/compliance stakeholders at Nexteer Automotive to deliver an AI document comparison tool with traceability and confidence indicators, adopted by non-technical users and saving ~2 FTEs of review time.”
Senior Software Engineer specializing in cloud backend systems and LLM-powered agents
“Amazon Fire TV Devices engineer who built and shipped a production LLM-powered lab triage and validation system that grounds recommendations in internal runbooks/known-issue data and pushes evidence-based actions via dashboards and Slack. Emphasizes safety and measurability with structured JSON outputs, replay-based evaluation on historical incidents, and production metrics (e.g., disagreement rate and time-to-first-action), plus cost/latency optimizations like caching, batching, and rule-based fast paths.”
Mid-Level Software Engineer specializing in cloud-native systems, automation, and LLM-enabled robotics
“React-focused engineer who built a full-stack analytics/test-metrics dashboard (React frontend + Python backend) and turned common UI pieces (data tables, filter panels, chart wrappers) into a reusable internal component library with docs, examples, and basic tests. Strong on profiling-driven performance optimization (React Profiler, memoization) and on owning ambiguous internal-tool projects end-to-end; now planning to package internal patterns into public open-source components.”
Mid-Level Software Engineer specializing in Python automation, DevOps, and microservices
“Backend-focused engineer who built an internal wiki LLM chatbot end-to-end using FastAPI, Kubernetes, and ChromaDB vector search, including frontend integration. Also has strong DevOps/migration experience—automating large work-item and repo migrations (Jira/FogBugz/ADO on-prem to cloud) via Python scripts, JSON mappings, REST APIs, and validation test suites.”
Mid-Level Software Engineer specializing in distributed systems and cloud-native platforms
“Backend/AI engineer who built and scaled an internal AMD semiconductor manufacturing microservice platform (SMR), reworking a synchronous lot-request workflow into an event-driven RabbitMQ/Celery/FastAPI pipeline. Diagnosed and fixed peak-load reliability issues using deep observability and Kubernetes autoscaling, cutting notification latency back to sub-second and reducing duplicates via idempotency/DLQs. Also shipped an LLM-powered natural-language search with schema-constrained JSON outputs and guardrails, plus a plan-execute-verify Jira bug-resolution agent that can propose fixes and raise PRs under restricted permissions.”
Executive Marketing Leader specializing in MarTech, CRM, and digital growth
“Marketing/CRM professional who has built a CRM and marketing department from scratch—starting with Excel, then integrating into a formal CRM—using segmentation by geography (zip code/geofencing) and profession. Has run retention and lifecycle programs across both B2B and B2C via email/newsletters/social, with A/B testing experience and exposure to major clients including Fox and Sony.”
Mid-level Full-Stack Developer specializing in cloud microservices and AI/ML integration
“Full-stack engineer (~3 years) with eBay production experience building and operating high-scale, event-driven Python microservices for order processing and AI-powered recommendations (Kafka/Redis/FastAPI on AWS with Prometheus/Grafana). Also delivered polished React+TypeScript analytics dashboards and designed high-concurrency PostgreSQL schemas with significant latency reductions. Recently built AI-agent orchestration and an interactive node-based requirements dashboard for Siemens Polarion via MCP servers, improving user interaction by ~17.8%+.”
Junior Software Engineer specializing in cloud developer tools and backend APIs
“Summer intern on AWS Lambda tooling team who shipped Finch support in AWS SAM CLI, adding OS/runtime detection and robust fallback behavior to preserve Docker compatibility across developer environments. Also built an end-to-end RAG system for querying arXiv quantitative finance papers using Postgres/pgvector with two-stage retrieval, citation-grounded prompting, and rigorous evaluation loops driven by IR metrics and user feedback.”