Pre-screened and vetted.
Mid-level AI Engineer and Data Scientist specializing in LLM agents and RAG systems
“Built a production-grade LLM evaluation and regression system that stress-tests models across hundreds of iterations, combining LLM-as-judge, semantic similarity, statistical metrics, and rule-based checks, with results delivered via stakeholder-friendly HTML reports and dashboards. Experienced orchestrating multi-agent RAG workflows using LangChain/LangGraph and event-driven GenAI pipelines in n8n integrating OCR, speech-to-text, and external APIs, with strong emphasis on reliability, observability, and explainable failures.”
Mid-Level Software Engineer specializing in backend systems, cloud, and applied LLM/NLP
“Applied LLMs to classify long nonprofit mission statements into 8 segments without labeled data, using an ensemble of clustering/embedding methods plus zero-shot RoBERTa/BART and a Tree-of-Thought prompting pipeline with LLM-as-judge evaluation (Gemma). Also built LangChain/LlamaIndex agentic RAG workflows including a text-to-SQL data analysis assistant grounded on DB schema with retries and performance optimizations on an HPC cluster.”
Mid-level Software Engineer specializing in full-stack development, data engineering, and GenAI
“Built and deployed an LLM product called "Content Craft" combining BART-based summarization with a RAG Q&A chatbot using LangChain, embeddings, and a vector database. Has hands-on MLOps experience containerizing and serving models with FastAPI and running them on Kubernetes with monitoring, self-healing, and autoscaling, and has practical experience reducing hallucinations through structured prompting.”
Entry Software QA Engineer specializing in manual, automation, and API testing
“Mobile QA tester with hands-on manual testing experience (functional flows, UI/UX checks) and disciplined documentation/bug tracking in JIRA. While new to console testing and TRC/XR/LOT certification requirements, they describe a concrete ramp-up plan (study guidelines, review standards, shadow experienced testers) and emphasize clear defect communication and deadline-driven prioritization.”
Junior Software Developer specializing in Oracle APEX and enterprise integrations
“Oracle Software Developer (2+ years) at C3 Business Solutions, a consulting firm building and maintaining ERP applications across Oracle APEX/FDI/Fusion/EBS/OCI. No formal game QA experience yet, but demonstrates practical QA-adjacent skills (test planning, debugging via logs, and detailed bug reporting) and is explicitly looking to transition into a QA Engineer role.”
Mid-level QA Engineer specializing in test automation and CI/CD quality validation
“QA Automation Engineer with hands-on ownership of an end-to-end Selenium-Java/TestNG suite for an e-commerce platform, integrated into Jenkins with PR smoke and nightly regression gating. Notably caught and validated (via SQL/API checks) a critical defect where checkout reported success but orders were not persisted, preventing customer-impacting production issues; also has Cypress experience stabilizing flaky UI tests using robust selector and wait strategies.”
Junior Full-Stack & LLM Engineer specializing in AI agents and cloud document intelligence
“Backend engineer specializing in event-driven/serverless systems and Python/FastAPI APIs. Built a scalable PDF-to-structured-data pipeline on AWS (S3, Lambda, Step Functions, Textract, DynamoDB, SNS) with strong observability (p50/p90/p99) and reliability patterns (idempotency, retries/DLQs), and has led zero-downtime migrations using feature flags, dual writes, and incremental rollouts.”
Executive Full-Stack Developer specializing in HealthTech and AI
“Frontend-focused builder who worked on the VITALES.LIFE healthcare app using Next.js/React Native alongside multiple backend technologies (NestJS, Go, Python/FastAPI) on Firebase/GCP. Has experience delivering client-driven MVPs (e.g., Omnicommander, Talentus) and uses Jest for test coverage while emphasizing code reuse and non-duplicative components.”
Intern Full-Stack/Backend Engineer specializing in cloud-native APIs and event-driven systems
“Backend-focused engineer who built an academic AI voice assistant with a Python microservice-style backend (speech recognition, spaCy-based NLP, and Kafka-driven automation) optimized to sub-500ms latency. Also has Sodexo internship experience deploying containerized services across Kubernetes/AWS ECS/Azure using ArgoCD GitOps, including solving config drift and secret-management challenges and supporting cloud-to-on-prem migrations with blue-green rollouts.”
Mid-level Java Full-Stack Developer specializing in cloud-native microservices
“Full-stack engineer from Clairvoyant who led end-to-end delivery of a cloud-native, event-driven platform: Spring Boot microservices + Kafka real-time streams with an Angular UI, migrated and containerized on AWS, and automated CI/CD with Jenkins/Maven/Git. Demonstrates depth in distributed consistency challenges (partitioning, consumer lag/duplicates) and database performance tuning across SQL/NoSQL under heavy workloads.”
Junior Full-Stack Engineer specializing in AI and automation
“Startup-focused builder who created and iterated an MVP for Enky, a two-sided marketplace connecting music artists and creators, informed by hundreds of customer interviews. Implemented CI/CD, monitoring (PostHog/Sentry), and a complex payout pipeline involving scraping social platforms and routing escrow payments via Stripe, and has a track record of quickly debugging production issues (e.g., iOS-specific OAuth cookie failures).”
Senior SDET specializing in test automation and CI/CD for web, mobile, and API testing
“Software/automation QA professional with hands-on Oculus VR testing at Telkom, covering controller inputs, tracking reliability, performance/FPS stability, thermal behavior, crash reproduction, and system-level events (standby/resume, low battery, network interruptions, guardian changes). Familiar with the intent and coverage areas of console certification frameworks (Sony TRC/Microsoft XR/Nintendo LOTcheck) and uses AI to speed up log analysis and test case creation.”
Mid-Level Software Engineer specializing in AI/ML and cloud-native platforms
“Backend/AI engineer who has built production LLM orchestration and agentic workflow systems in Python/FastAPI on Kubernetes across AWS/Azure. Demonstrated strong reliability engineering by debugging a real-world memory retention issue that caused latency spikes/timeouts, and strong data/performance chops with a PostgreSQL optimization that cut query latency from ~1.2s to ~15ms. Targets roles building scalable, guardrailed AI-driven workflow automation with robust observability and human-in-the-loop controls.”
Senior Test Automation Engineer specializing in mobile UI/API automation and CI/CD
“QA automation engineer (Tencent experience) who extended Android Monkey testing to dramatically increase activity coverage (~300%) and cut runtime from 8 hours to ~1 hour per app. Strong in Cypress/JS test architecture and CI/CD gating (GitLab + Kubernetes parallel runs), and has a track record of reproducing and documenting high-impact reliability issues (e.g., silent failures in a cloud-native mobile automation platform under network loss).”
Senior Software Engineer specializing in Backend Systems and Generative AI (RAG)
“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 AI/ML Software Engineer specializing in Generative AI and scalable data pipelines
“Built and operated large-scale biodiversity/ecological research platforms, integrating 50+ heterogeneous global datasets into a unified BIEN 3 schema on PostgreSQL/PostGIS and improving data consistency by 35%. Strong production engineering background (Linux monitoring, CI/CD performance gates, Docker on AWS/Azure) plus applied AI work building a Python RAG system (0.90 precision) and halving latency with Elasticsearch.”
Junior Data/AI Engineer specializing in MLOps, real-time pipelines, and LLM applications
“Built an LLM-driven MLOps agent at SBD Technologies that automated an EV-charging prediction workflow end-to-end, integrating with real-time Kafka/FastAPI systems supporting 120K+ chargers at 99.99% event delivery. Addressed frequent schema drift by implementing SQLAlchemy/Flyway validation (60% reduction in drift issues) and deployed as Kubernetes microservices with GitHub Actions CI/CD; also has Airflow-based ingestion/crawling experience into Snowflake and stakeholder-facing delivery via a Fleetcharge PWA.”
Senior System Analyst specializing in software QA and FinTech payments
“Indonesia-based software tester with hands-on experience testing payment software on EDC machines and manual web application QA, plus early exposure to Selenium automation. Pragmatic about deadline-driven triage—prioritizes critical issues and plans lower-impact fixes for future patches—while expressing strong interest in learning game-industry standards.”
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.”
Mid-level Operations & Client Success Manager specializing in process automation and vendor management
“Sales/business development professional with experience in high-value client account expansion and partner acquisition (including real estate sales/property management) who also self-taught Python and built a Selenium-based automation system to eliminate manual booking work. Demonstrated measurable impact across both revenue/relationship outcomes (profit margin lift, high CSAT) and operations (70% faster bookings, 95% fewer errors, 25%+ efficiency gains).”
Senior Full-Stack & AI Developer specializing in Python/React, AWS, and LLM/RAG systems
“Backend Python engineer who owned the full backend build of an AI-driven platform for UK golf clubs, including FastAPI microservices, vector search, and a tuned LangChain+Pinecone RAG pipeline focused on cost and hallucination reduction. Experienced deploying Django/FastAPI/Flask stacks on AWS-backed Kubernetes with GitOps/ArgoCD-style delivery, plus executing legacy-to-AWS migrations and building Kafka-based real-time analytics pipelines.”
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.”
Executive CTO / Engineering Leader specializing in Full-Stack Architecture and Cloud Delivery
“Founder building a hiring-focused startup who has engaged with venture investors but is prioritizing direct end-user traction through email marketing and other outreach before returning to raise a seed round. Has experience working with startups that have already raised seed funding and demonstrates a structured approach to market validation (customer conversations, landing pages) prior to heavy development.”
Intern Data Scientist specializing in machine learning, NLP, and LLM fine-tuning
“Built a production-style AI meeting summarization and action-item extraction system (Azure Speech-to-Text + transformer summarization/NER) exposed via a Flask REST API, with explicit guardrails to prevent hallucinated tasks. Strong focus on reliability: modular agent/workflow design, precision-first evaluation with human-validated golden notes, and practical orchestration patterns (tool-augmented agents; ready to scale into Airflow/LangGraph/Prefect).”