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Vetted SQLite Professionals
Pre-screened and vetted.
Mid-level Software Engineer specializing in APIs, data systems, and automation
Intern Data Scientist specializing in machine learning, forecasting, and LLM applications
Senior Frontend Software Engineer specializing in SaaS DevOps platforms
Mid-level Full-Stack Developer specializing in cloud-native web applications
Entry-Level Software Engineer specializing in data analytics and full-stack development
Engineering leader specializing in cloud-native regulated healthcare SaaS
Senior Full-Stack Software Engineer specializing in Healthcare IT and FinTech integrations
Junior Software Engineer specializing in systems, security, and full-stack development
Senior Machine Learning Engineer specializing in GenAI, LLMs, and MLOps
Senior Machine Learning Engineer specializing in GenAI, LLMs, and MLOps
Junior Full-Stack Software Engineer specializing in AI systems and cloud infrastructure
Senior Full-Stack Engineer specializing in compliance, integrations, and data platforms
Principal Automation Architect specializing in cloud DevOps, microservices, and MLOps
Harshini Kanamathareddy
Mid Software Engineer specializing in iOS, backend systems, and AI-powered applications
“Full-stack/backend engineer with experience spanning React/TypeScript, Flask, Spring Boot, SQL databases, and production mobile optimization. They’ve shipped features end to end, improved query performance and app startup/crash metrics, and helped drive a configuration-driven architecture that enabled faster releases across 30 consumer applications.”
Aniruddha Rajnekar
Mid-level Full-Stack Engineer specializing in FinTech and cloud-native systems
“Full-stack engineer with about 3 years of experience who is deeply hands-on with AI-assisted development and agentic systems. Built TubeAgent using LangChain, Ollama, FAISS, and Llama 3, and has demonstrated measurable impact by cutting review time by 90% and reducing deployment time from 30 minutes to under 5 minutes at NC State. Combines practical experimentation with strong architectural thinking around resilient, composable AI systems.”
Anirudh Herady
Junior Software Engineer specializing in backend systems and LLM/RAG applications
“Full-stack engineer who built a cloud storage app feature (file upload/management) with Next.js App Router + TypeScript and owned post-launch improvements. Also has internship experience building a geospatial AI chatbot: designed Postgres/PostGIS data models and optimized spatial queries, and implemented an LLM workflow orchestrated with LangChain/LangGraph plus a RAG pipeline grounded in OpenStreetMap data to reduce hallucinations.”
Rama Gowtham Reddy Padala
Mid-level Backend Python Engineer specializing in APIs, microservices, and data pipelines
“Backend engineer (Marsh McLennan) who evolved a high-volume claims automation pipeline in Python, emphasizing thin APIs with background job processing, strong validation/retries, and production-grade observability. Experienced in secure FastAPI API design (centralized JWT/RBAC), multi-tenant Postgres/Supabase-style row-level security, and low-risk refactors using parallel runs and feature flags; targeting founding-engineer scope roles.”
Teage Johnson
Junior Full-Stack Engineer specializing in FinTech and machine learning
“Software engineer at early-stage startup Cari with hands-on experience shipping AI-enabled production workflows, including an LLM chatbot for a micro-transit platform and an automated image-processing pipeline integrated with Claude. Stands out for combining practical agent reliability patterns—schema validation, fallbacks, caching, and idempotency—with strong ML evaluation instincts and experience cleaning messy operational invoice data.”
Wyatt Fong
Entry-level Full-Stack Software Engineer specializing in AI and healthcare tech
“Built a Python pipeline to monitor and classify public posts from sources like Hacker News and Reddit for SWE/tech job opportunities, with a strong focus on reliability, observability, and recoverable failures. Also currently building a court queueing system for the UCSD Badminton Club, showing an ability to turn messy, informal real-world processes into practical automation through iterative user feedback.”