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Vetted Containerization Professionals
Pre-screened and vetted.
Senior QA Automation Engineer (SDET) specializing in Java test automation and CI/CD
Senior DevSecOps Engineer specializing in CI/CD and Kubernetes security
Entry-level Full-Stack Software Engineer specializing in streaming infrastructure
Junior Full-Stack Software Engineer specializing in Python, React, and AWS
Mid-Level Full-Stack Software Engineer specializing in Java/Spring and React/Node microservices
Mid-Level Full-Stack Software Engineer specializing in AWS and RAG pipelines
Mid-level Full-Stack Developer specializing in Python, React, and cloud-native microservices
Junior Full-Stack Software Engineer specializing in cloud-native microservices and data pipelines
Mid-Level Software Engineer specializing in Java/Spring Boot microservices and cloud platforms
Ramis Hasanli
Intern Cybersecurity Engineer specializing in AI agents and production workflows
“Built and deployed an AI customer representative for iCore used at the IEE convention (2025), serving 100+ users in a day; implemented RAG with a vector database and scaled reliability via Docker and Google Cloud. Also has hands-on experience with multiple agent orchestration stacks (LangChain/LangGraph, Google AI Agent Development Kit, OpenAI SDK, Composio) and has delivered stakeholder-driven apps using prototyping and MVP scoping.”
Diego Hernandez
Entry-level Mechatronics Engineer specializing in robotics, automation, and ROS 2
“Robotics software/embedded engineer who helped build an end-to-end perception sensor platform in a two-person team, owning PCB design, ROS architecture (sensor/processing/diagnostic nodes), and documentation. Experienced integrating heterogeneous sensors over CAN with Arduino and optimizing real-time performance bottlenecks (camera and high-frequency streams) using compression, grayscale pipelines, and reduced inference frequency; also containerized the system with Docker.”
Intern Full-Stack Software Engineer specializing in AI-powered applications
Maulik Maganbhai Ghatala
Entry Backend Software Engineer specializing in Python/FastAPI and cloud-native APIs
“Backend engineer who built and evolved a low-latency document search platform (C++/gRPC on Kubernetes with a vector database), emphasizing resilience under concurrent load through strict deadlines, retries, idempotency, and observability. Also experienced building secure, frontend-friendly FastAPI services (Pydantic + JWT) and executing safe incremental refactors using feature flags and parallel validation.”
Junior Full-Stack Data Engineer specializing in data pipelines and analytics
Junior Full-Stack Software Engineer specializing in SaaS and FinTech systems
Junior Full-Stack Software Engineer specializing in React/Next.js and TypeScript
Entry-Level Full-Stack Software Engineer specializing in backend systems and cloud deployment
Andrew Douangprachanh
Entry-level Full-Stack Software Engineer specializing in web and real-time applications
“Frontend-focused developer who built Brick-Verse, a React/TypeScript CRUD app combining Spring Boot, Spring Security, JWT auth, PostgreSQL, and the Rebrickable API. Stands out for handling multi-source data flow, protected user features like favorites, and practical React performance and responsive CSS challenges in a production-style project.”
“Built AI-powered features for a learning management system, including file-to-quiz generation with Gemini, strong validation/security controls, and teacher review workflows for contested AI grading. Stands out for combining full-stack product delivery with practical LLM safety measures like prompt-injection prevention, structured output validation, sanitization, and rate limiting.”
Intern/Junior Software Engineer specializing in full-stack web development and machine learning
Anjali Chepuri
“Built and deployed an LLM-powered financial document processing and summarization platform at Morgan Stanley using a production RAG pipeline (PDF ingestion, embedding-based retrieval, schema-constrained JSON outputs) delivered via FastAPI microservices on Kubernetes. Drove measurable impact (40% reduction in manual review time) and improved factual accuracy for numeric fields by 30% through metadata-aware retrieval, strict schemas, and post-generation validation, with a human feedback loop from financial analysts.”