Pre-screened and vetted.
Senior Full-Stack & AI/ML Engineer specializing in cloud-native SaaS and IoT analytics
Executive Engineering Leader specializing in cloud-native platforms and security
“Former CTO of EzCred, a fintech embedded finance/digital lending infrastructure startup that built an API-first underwriting and servicing platform using alternative data (e.g., GST and bank statements) to cut loan decisions from days to minutes. Helped raise $1M in seed funding, built the engineering org and compliance-ready cloud architecture, and ran partner pilots before the company shut down during COVID-driven lending market contraction.”
Senior Software Engineer specializing in scalable backend and platform systems
“Backend/data engineer with hands-on production experience across GCP (FastAPI microservices on Kubernetes) and AWS (Lambda, ECS Fargate, Glue). Has modernized legacy SAS batch systems into Python services with parallel-run parity validation, and has strong operational rigor in ETL reliability/monitoring plus proven SQL tuning impact (25s to <300ms, ~60% CPU reduction).”
Senior Full-Stack Engineer specializing in web platforms and mobile apps
“Backend/platform engineer with experience at Microsoft, Uber, and Gusto building production AI-agent automation systems in Python (AutoGen) and cloud-native microservices on Kubernetes across AWS/Azure. Has delivered zero-downtime migrations and high-throughput real-time streaming pipelines (Kafka/WebSockets/Redis), and is strong in GitOps/ArgoCD-driven CI/CD with reliable rollouts and rapid rollback.”
Mid-level Full-Stack Developer specializing in cloud-native web applications
“Frontend-leaning full-stack engineer who built an internal real-time operations dashboard from 0→1 using React, TypeScript, Redux Toolkit, Material UI, and Node.js integrations. Stands out for hands-on performance tuning at scale—profiling and fixing excessive re-renders, optimizing live-update UIs, and iterating post-launch with caching, pagination, and observability.”
Senior Software Engineer specializing in cloud-native SaaS and event-driven microservices
Senior Software Engineer specializing in full-stack web platforms and cloud-native backend systems
Senior Full-Stack Software Engineer specializing in cloud-native distributed systems
Staff Software Engineer specializing in real-time data pipelines and full-stack platforms
Senior Full-Stack Engineer specializing in cloud-native web applications
Staff Full-Stack Engineer specializing in cloud microservices and AI-enabled platforms
Senior Software Engineer specializing in AI/ML tooling and data platforms
Staff Software Engineer specializing in cloud-native AI and supply chain platforms
Senior Software Engineer specializing in full-stack, AI/ML, and cloud platforms
Senior Full-Stack Software Engineer specializing in cloud-native microservices
Staff Full-Stack & AI Engineer specializing in LLM platforms and scalable cloud systems
Staff Software Engineer specializing in streaming platforms and AI-driven experiences
Mid-level Full-Stack Developer specializing in cloud-native microservices
Senior Full-Stack Engineer specializing in FinTech and fraud/risk systems
Senior Software Engineer specializing in cloud platforms for healthcare and e-commerce
Senior Backend Engineer specializing in Node.js, Java, and regulated SaaS platforms
“Built a production LLM-powered root cause analysis agent for supply chain alerts that helped operations managers avoid manual dashboard investigation. Demonstrates unusually strong depth in agent reliability, orchestration, and observability, with concrete production practices like hallucination blocking, shadow testing on 500 cases, and data-driven improvements that raised user agreement to 94% while cutting GPT-4 usage by 60%.”
Senior AI/ML Data Scientist specializing in recommender systems, LLMs, and MLOps
“ML/NLP leader with 12+ years of impact across LinkedIn, TikTok, and Levi's, building and productionizing multimodal recommendation and embedding-based search systems. Deep experience in entity resolution, vector retrieval, and rigorous evaluation, with cloud-native deployment/monitoring (MLflow, Airflow, SageMaker/Lambda, Azure ML, Kubernetes) and demonstrated double-digit relevance gains at millions-of-users scale.”