Vetted Snowflake Professionals

“Full-stack engineer with hands-on ownership of production systems, including a Kafka-based notification/alerting platform (Node.js + React) deployed on AWS with Docker/GitHub Actions, achieving ~95% email delivery reliability. Demonstrates strong operational maturity (observability, CI/CD, zero-downtime migrations) and experience shipping in ambiguous environments (SJSU project) with evolving requirements.”

“Data engineer focused on building reliable, production-grade pipelines and data services end-to-end, including a 50+ GB/day pipeline ingesting from APIs/files into Snowflake with PySpark/SQL transformations. Emphasizes strong data quality controls, monitoring/retries, and performance optimization, and has also shipped a Python data API with caching and backward-compatible versioning.”

“ML/NLP engineer who has built production systems end-to-end: a real-time recommendation platform (100k+ profiles) using BERTopic-style clustering and a RAG-based news summarization/recommendation stack with ChromaDB. Strong focus on scaling and reliability (GPU batching, Redis caching, Kafka ingestion, Docker/Kubernetes, Prometheus/Grafana) and on maintaining model quality over time via drift monitoring and retraining triggers.”

Venkata Bayarapuneni

Screened

Junior Full-Stack Developer specializing in JavaScript, Python, and cloud-deployed web apps

Remote, USA1y exp

“Built and deployed a production LLM-powered travel assistant (Globe Trote) that automates end-to-end trip planning using a multi-step agent pipeline with RAG, external API calls, and enforced structured JSON outputs. Focused on reliability (validation, retries, fallback prompts, logging) and reported a ~30–40% reduction in irrelevant/generic responses after adding retrieval grounding.”

SaiDheerajReddy Gadikota

Screened

Mid-level AI Engineer specializing in agentic systems and enterprise LLM platforms

USA, USA4y exp

“Current AI engineer at a startup who has spent the last year architecting multi-agent systems for software development workflows. Stands out for combining LLM speed with engineering discipline—using tools like Pydantic, LangGraph, and LangChain to build reliable, production-ready agent workflows with validation, routing, and retry logic.”

“Research Analyst at Syracuse who deployed an LLM-powered lab automation system allowing researchers to run QCoDeS instrument workflows via natural language, with strong safety guardrails for real instruments and multi-instrument support. Also collaborated with non-technical stakeholders at iConsult on an audio classification/recommendation pipeline, translating business goals into metrics and Tableau dashboards with model comparisons and A/B test results.”

Dhairya Gajjar

Screened

Mid-Level Software Engineer specializing in Healthcare Data Platforms

Remote2y exp

“Backend/ML engineer with healthcare domain experience building secure Medicare/Medicaid data APIs and real-time patient risk scoring. Shipped an end-to-end ML pipeline (scikit-learn/XGBoost) served via SageMaker and integrated into Flask APIs, with strong production reliability practices (Kafka schema validation, regression replay, observability, drift monitoring, and human-in-the-loop guardrails).”

“Backend engineer who built and scaled a FastAPI-based backend for an AI-driven maintenance system automating vendor sourcing/bidding/communication. Emphasizes async, message-driven architecture with strong observability and state-machine-driven workflows, plus robust webhook/idempotency patterns to prevent duplicate/out-of-order events from causing bad bids or state changes.”

“Internship-built full-stack systems spanning HR employee-record portals and internal data-quality dashboards (Flask + SQL + React), emphasizing data integrity and rapid MVP iteration. Also implemented Flask microservices with RabbitMQ for distributed task processing, addressing duplication/ordering issues with idempotency, durable queues, and correlation-ID logging; delivered quantified productivity gains for HR teams.”

John Kenny

Screened

Senior Full-Stack Engineer specializing in Web3 and FinTech

Global, Remote6y exp

“Full-stack engineer with deep startup experience (pre-seed through IPO/SPAC) currently building a Next.js/TypeScript SaaS sports analytics platform with a complex Postgres-based entitlement/ACL system. Has delivered measurable UX/business impact (35% retention lift, 40% volume increase) and built production-grade daily ETL + model training/inference workflows with validation and checkpointing for reliability.”