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Vetted NoSQL Professionals
Pre-screened and vetted.
Mid-level Backend Engineer specializing in cloud and distributed systems
Mid-level AI Backend Engineer specializing in LLM applications and scalable ML services
Mid-level Backend Software Engineer specializing in microservices and cloud APIs
Mid-Level Software Developer specializing in FinTech and AI-enabled systems
Mid-level AI/ML Engineer specializing in GenAI, RAG, and cloud-native ML platforms
Mid-level AI/ML Engineer specializing in recommender systems, NLP, and MLOps
Mid-level Full-Stack Developer specializing in .NET, Python/Django, and cloud-native web apps
Mid-Level Full-Stack Software Engineer specializing in FinTech and AI risk scoring
Mid-level AI Data Scientist specializing in financial risk, fraud detection, and NLP/LLM systems
Junior Multimodal AI & Systems Engineer specializing in robotics and cloud infrastructure
Intern Software Engineer specializing in cloud governance and distributed systems
Mid-level Data Engineer specializing in cloud lakehouse and streaming pipelines
Mid-level AI Backend Engineer specializing in LLM applications and scalable ML systems
Khaliun Gerel
Senior Full-Stack Engineer specializing in cloud, web, and mobile platforms
“Full-stack product engineer who has owned end-to-end delivery of multi-client platforms: Finy (agriculture platform with 3 role-based web dashboards plus 2 field mobile apps) and Ugoku (Japanese studio platform with React/TypeScript dashboards, Node/Mongo backend, and mobile AR video playback). Strong in scalable architecture and performance—offline-first mobile for low connectivity, and AWS-based asynchronous video/AR processing with S3/CloudFront—plus building internal ops tools adopted quickly due to measurable workflow improvements.”
Longyang Xu
Junior Full-Stack Software Engineer specializing in cloud microservices and ML-driven products
“Backend engineer with hands-on ownership of Python/Flask microservices and recommendation systems across edtech and telecom. Deployed and operated real-time personalization/recommendation platforms on AWS EKS with Jenkins-based CI/CD, GitOps-style declarative configs, and strong observability practices. Has migration experience moving legacy mixed environments to modern containerized Kubernetes and built Kafka pipelines feeding ML services while managing schema evolution.”
Jenny Cheng
Junior Full-Stack/ML Engineer specializing in LLM applications and cloud deployment
“Full-stack developer with capstone and project experience delivering production-ready systems in unstructured environments, including a Faculty Tracking system for real departmental use. Strong in React performance debugging (re-render optimization with useMemo), Prisma-backed multi-database setups (MySQL local / SQL Server production on a UCI Health VM), and end-user support workflows that feed back into improved Help documentation.”
Meet Merchant
Mid-level Software Engineer specializing in LLM agents and full-stack systems
“At Esri, the candidate is building a production LLM-powered WebGIS AI framework that embeds an AI assistant into web maps and routes natural-language requests into ArcGIS JavaScript SDK functions via a LangGraph-orchestrated, multi-agent system. They emphasize production reliability and scale (strict tool calling/JSON, live schema validation, query guardrails) and rigorous evaluation/observability using LangSmith, offline prompt datasets, and latency/tool-call accuracy tracking.”
mahesh narne
Senior Full-Stack Software Engineer specializing in cloud-native microservices and web apps
“Backend-focused engineer building customer support/order-tracking platforms with Java 17/Spring Boot microservices and a React/TypeScript frontend. Deep experience running event-driven systems on Kubernetes (Kafka, Redis, MySQL) with strong observability (Prometheus/Grafana/Splunk), SLOs, and safe deployment practices (feature flags, canaries). Also built an internal monitoring/debugging dashboard that consolidated metrics and logs for on-call engineers and was adopted by other teams to speed incident response.”
Shankar Koduvayur Ramaswami
Mid-level Machine Learning Engineer specializing in industrial deep learning and predictive control
“AI engineer building and deploying deep-learning-based optimization/control systems for petrochemical plants, with a focus on maintaining operational stability under real-world constraints. Core contributor to model and inference design; introduced a stability-focused non-linear objective and sped up second-layer optimization via on-the-fly first-order approximations. Experienced using Kubernetes for end-to-end testing and effective in translating customer expectations into measurable evaluation plots for non-technical stakeholders.”