Pre-screened and vetted.
Principal Full-Stack Engineer specializing in AI, DevOps, and cloud platforms
“Built a production end-to-end AI video-to-reels clip extraction system using a multi-agent architecture with transcription, captioning, effects generation, and centralized orchestration. Demonstrates unusually strong systems thinking around reliability, observability, evaluation, and production tradeoffs for LLM-powered workflows, including Kubernetes/Kafka-based deployment and regression-driven prompt governance.”
Entry-level ML Systems Engineer specializing in LLM infrastructure and recommender systems
“Engineer with a mature, agent-oriented approach to AI-driven software development, using structured planning, TDD, and verification loops rather than ad hoc prompting. Has hands-on experience acting as a tech lead for multiple AI agents in an LLM intelligent routing project, coordinating implementation, testing, debugging, and edge-case review with strong attention to system tradeoffs.”
Mid-level Full-Stack Engineer specializing in real-time data and AI systems
“Software engineer focused on backend/full-stack, distributed systems, cloud infrastructure, and AI-related work. Stands out for using AI and multi-agent workflows as an engineering accelerator while maintaining rigorous testing, logging, and system-level validation, including work on telemetry and monitoring platforms where reliability and correctness are critical.”
“Full-stack engineer with hands-on experience leading early AI product initiatives, including a RAG dashboard prototype and a production-ready agentic workflow integrating Front, Airtable, and Slack. Stands out for combining Angular/TypeScript frontend leadership with FastAPI backend work, plus a strong focus on evals, observability, and hardening LLM systems before launch.”
Mid Software Engineer specializing in backend and FinTech systems
“Full-stack AI engineer who built HireMate end to end using FastAPI, React, and TypeScript to automate resume-to-job matching and tailoring with LLMs. Demonstrates strong practical judgment around grounding, validation, hallucination prevention, and human-in-the-loop design, and has also shipped an early-stage multi-agent rental research workflow that processed 200-300 listings in parallel.”
Senior Python Developer specializing in FastAPI, Django, and cloud-native web applications
“Backend engineer working on Plumas Bank’s digital modernization, building a FastAPI-based loan origination/processing system with OAuth2/JWT security, AWS Lambda-driven PDF document generation to S3, and MongoDB integration. Has led a legacy workflow migration to a new microservice using dual-write/dual-read and monitoring, and emphasizes multi-tenant isolation via layered API controls plus row-level security.”
Mid-level Full-Stack Java Engineer specializing in banking microservices and AI backends
“Backend-focused software engineer building distributed, event-driven Java/Spring Boot microservices with Kafka for low-latency, high-frequency processing. Has hands-on experience modernizing a legacy Java system into containerized microservices deployed on Kubernetes with GitHub Actions CI/CD, and has integrated retrieval-based AI components into production workflows; no ROS/robot hardware experience yet.”
Mid-level AI/ML Software Engineer specializing in data pipelines, BI dashboards, and computer vision
“Graduate Assistant Intern at Friends University who built and deployed a GenAI-driven requirement understanding system that automates extraction and semantic grouping of technical requirements from large unstructured documents. Demonstrates strong LLM engineering rigor (golden datasets, regression testing, post-processing validation) and production-minded delivery using LangChain/LlamaIndex orchestration, FastAPI microservices, Docker, and cloud deployment.”
Junior Robotics & AI Engineer specializing in autonomous systems and 3D perception
“Robotics software engineer who led system design for an Autonomous Trash Collecting ASV presented at the IEEE ICRA 2025 “Robots in the Wild” workshop, integrating YOLOv8-based perception with ROS autonomy logic to detour for trash while preserving a scientific survey mission. Also built ROS2 UAV capabilities combining ArUco detection, RTAB-Map SLAM, and PX4 integration, with strong simulation (Gazebo/VTD/MSC Adams) and CI/CD QA automation experience.”
Senior Game Operations Specialist in live ops, QA, localization, and community management
“Game QA professional with hands-on PC/mobile testing experience on major titles including Call of Duty Mobile and PUBG Lite at Garena Indonesia. Has run full-cycle functional/regression testing plus live ops coordination across multiple regions, using standardized bug/reporting workflows and dashboards to keep distributed teams aligned. Familiar with the intent of console certification-style requirements (UI consistency, error handling, save/load, localization formatting) despite not having direct TRC/XR/LOT submission experience.”
Mid-level Applied AI/ML Engineer specializing in agentic systems and LLM automation
“Built a production LLM-powered workflow at Frontier to extract structured signals from messy, high-volume documents and route work to the right teams, replacing a multi-day, error-prone manual process. Emphasizes production reliability with schema/consistency validation, re-prompting and deterministic fallbacks, plus async pipeline optimizations for predictable latency. Experienced with multi-agent orchestration (LangGraph, AutoGen, CrewAI) and AWS workflow tooling (Step Functions, SQS, Lambda), and delivered ~70% safe automation via stakeholder-driven thresholds and human review.”
Senior Platform Engineering Lead specializing in AWS Cloud & DevSecOps
“Infrastructure/Platform-focused engineering leader who led a large-scale AWS modernization, standardizing Terraform IaC and embedding security/policy validation into CI/CD to reduce drift and improve auditability. Also delivered data reliability improvements by incrementally migrating key integrations to an event-driven Kafka model with DLQs and lag monitoring, and has hands-on incident leadership using observability tooling (New Relic).”
Mid-level QA Testing Analyst specializing in healthcare claims adjudication and PBM workflows
“QA automation engineer with strong Cypress/JavaScript experience in healthcare claims and eligibility systems, owning end-to-end regression suites that combine UI, API, and SQL/database validations. Known for catching subtle pricing/benefit calculation defects (copay/deductible/accumulator issues) before release, stabilizing flaky CI tests via API synchronization, and shaping requirements early to improve testability and reduce downstream rework.”
Junior Full-Stack Software Engineer specializing in Node.js microservices and React
“Backend engineer who has shipped both high-throughput real-time systems and production LLM/RAG features. Built a database-free, local-first messaging service (Node/Express/Socket.IO) achieving ~1,500 msgs/sec at <25ms p95, and implemented a Go-based RAG recommendation pipeline with strict JSON/schema validation, catalog grounding, fallbacks, and eval loops that cut hallucinations to ~1–2% while reducing LLM costs ~60%.”
Mid-level Full-Stack .NET Developer specializing in Azure, APIs, and Angular SPAs
“Frontend-focused engineer with enterprise Angular experience integrated with .NET APIs, emphasizing production-ready practices (reusable components, modular architecture, TypeScript standards, Jasmine unit tests, and CI/CD). Has not built Unreal Engine UI systems yet, but articulates how they would translate web UI modularity, separation of concerns, and testing/automation practices to Unreal/CommonUI workflows.”
Mid-level Full-Stack Developer specializing in healthcare analytics and microservices
“Built and maintained an air-quality prediction backend in Python/Flask that serves offline-trained ML models to a React dashboard via JSON REST APIs. Demonstrates strong performance focus across the stack—low-latency inference under load, SQLAlchemy/Postgres query optimization, multi-tenant data isolation, and caching/background task strategies for high-throughput systems.”
Mid-level QA Engineer specializing in Agile test planning and automation
“QA tester with hands-on API and web testing experience (functional, E2E, regression, sanity, performance) looking to transition into console game testing. Understands the need for platform-specific validation across console models/firmware and is aware of Sony TRC, Microsoft XR, and Nintendo LOT certification requirements, with a structured, risk-based approach to prioritization and release support.”
Mid-level Machine Learning Engineer specializing in cloud, governance automation, and distributed systems
“Governance engineer intern at GSK who built policy-as-code automation using Open Policy Agent/Rego integrated into GitHub CI/CD and Terraform workflows. Also built and shipped a voice-enabled expense tracking app using speech-to-text + LLM structured extraction with strong validation, retries, and semantic guardrails, and designed the supporting PostgreSQL data model with performance-focused indexing.”
Director-level Scrum Master / Technical Program Manager specializing in Agile delivery
“Director of Projects with experience owning HR operations processes from onboarding through exit and partnering with engineering to build/fix HRMS-related systems. Led cross-functional teams (engineering, QA, DevOps, operations, legal) to resolve data/tooling issues and improve operational rigor through Jira/Confluence documentation and multi-level code checks; also managed org-wide Jira licensing and user provisioning.”
Junior Machine Learning Engineer specializing in LLMs and RAG systems
“Production-focused applied ML/LLM engineer who has deployed an LLM-powered RAG assistant and improved reliability through rigorous retrieval evaluation (recall/MRR), reranking, and guardrails that prevent confident wrong answers. Experienced running containerized ML/LLM services on Kubernetes (including AWS-managed layers) with CI/CD and observability, and has delivered a real-time predictive maintenance system using streaming sensor data and time-series anomaly detection in close partnership with maintenance teams.”
Mid-level Full-Stack Software Engineer specializing in cloud-native microservices and FinTech
“At Delta Airlines, built and shipped a production LLM-powered semantic search/troubleshooting assistant over maintenance logs and operational documentation using OpenAI embeddings and a vector database. Implemented hybrid ranking, query enrichment, and structured filters to improve relevance ~35% while optimizing latency via caching and vector tuning. Also designed a scalable Kafka + AWS (Lambda/SQS) ingestion pipeline with strong reliability/observability and an eval loop using real engineer queries and human review.”
Mid-level Software Engineer specializing in backend and cloud-native microservices
“Backend/cloud engineer with 5 years of experience who has shipped a production internal ops LLM assistant end-to-end using Spring Boot microservices on AWS. Stands out for designing controlled, safety-first agent orchestration with deterministic tool access, Redis/DB-backed recoverable state, and strong observability/evaluation practices to improve reliability in production.”
Mid-Level Full-Stack Software Engineer specializing in React and Node.js
“Built and owned end-to-end TypeScript/React dashboards with a Node.js backend, including post-launch additions like role-based access and new reporting views enabled by modular architecture and clean API boundaries. Also created an internal real-time operations/engineering dashboard that replaced spreadsheets and reduced manual tracking, iterating quickly based on direct team feedback.”
Mid-Level Full-Stack .NET Developer specializing in cloud-native microservices and AI integration
“Software engineer with hands-on experience building and maintaining a React accessibility utility/component library (open-source-style) used across university portals, emphasizing WCAG 2.2 compliance, robust focus/keyboard behavior, and Jest/React Testing Library coverage. Also built and maintained .NET Core microservices at the Florida Department of Transportation, including integrating AI-driven features, with strong ownership around observability, incident response, and performance-focused refactoring.”