Vetted Flask Professionals

Sai Harsha Kurapati

Screened

Mid-level Backend Engineer specializing in distributed systems and industrial IoT

Indianapolis, IN4y exp

“Backend/Python engineer focused on real-time sensor/IoT analytics: built dashboards and a high-throughput ingestion pipeline (MQTT -> Python worker -> TimescaleDB) with buffering, batch inserts, and validation. Strong Kubernetes + GitOps practitioner (Dockerized microservices, HPA, probes, ArgoCD) who has handled production incidents like CrashLoopBackOff under peak load and supported an on-prem analytics migration to AWS using shadow traffic and rollback plans.”

Tamanna Nandlal Choithani

Screened

Entry-level Full-Stack Engineer specializing in AI and distributed systems

California, USA1y exp

“Full-stack engineer who built an AI-based inventory/procurement query system at Botlily/Botlerly using Flask and Google Sheets as a live knowledge base, overcoming Sheets latency with caching and structured in-memory models. Demonstrated strong LLM product engineering (40% accuracy improvement via preprocessing/prompting) and customer-driven iteration with bar/restaurant owners, evolving the tool into a more comprehensive inventory management and forecasting solution.”

“Built a production 13-step LLM agent pipeline at Sentari AI that converts diary entries into personalized AI responses and a persistent structured user profile. Stands out for a pragmatic approach to production AI: strict schemas, function calling, state-machine orchestration, confidence thresholds, logging, and validation layers to control non-determinism and prevent bad profile updates.”

Cristobal Troncoso

Screened

Senior Unity Developer specializing in VR, multiplayer, and AI-driven simulations

Santiago, Chile12y exp

“Unity/VR engineer who has owned systems from gameplay architecture through hardware integration, including a modular casino platform deployed to 100+ terminals in Chile that became the company’s primary revenue source for over three years. Also brings hands-on experience with AI-driven talking avatars, multiplayer VR training on Quest, and aggressive cross-platform optimization across WebGL, Android, and VR.”

“Built and owned enterprise data/integration deployments and production AI workflows, including a Python-based migration pipeline that moved 2M records with major improvements in onboarding speed, error rate, latency, and uptime. Also shipped a financial RAG assistant over 50K documents with sub-second p95 latency, showing a strong blend of customer-facing deployment ownership, data engineering, and LLM systems expertise.”

vinod yendluri

Screened

Mid-level MLOps Engineer specializing in production machine learning systems

Hyderabad, India3y exp

“Built an end-to-end churn prediction platform at Freddi's Flowers spanning Spark ETL on AWS, model serving, monitoring, and a stakeholder-facing dashboard. Stands out for combining MLOps rigor with product thinking—adding explainability, action-oriented workflows, and config-driven multi-tenant architecture while improving latency and automating drift response.”

“Full-stack/backend engineer with recent hands-on depth in Go, Python, React, and TypeScript, spanning telehealth, banking, and B2B workflow platforms. Particularly compelling for startup and scale-up environments: rebuilt core telehealth services to restore provider trust and support 150% user growth without adding servers, and has also delivered large-scale banking and compliance-sensitive systems in production.”

“Front-end engineer with strong experience building CMS-driven, headless e-commerce interfaces in Angular and React for retail brands including Shopify-based implementations and Bob's Discount Furniture. Stands out for combining reusable component architecture with measurable browser-performance gains, including ~25% faster rendering and improved Lighthouse scores, while enabling marketing teams to launch campaigns without engineering support.”

“ML engineer with hands-on experience building production AI systems spanning agentic AI, RAG, LLM automation, fraud detection, and predictive analytics. At Origami Risk, they designed and implemented an enterprise RAG platform end to end using LangChain, LangGraph, vector search, and AWS Bedrock to improve internal knowledge retrieval, reduce manual effort, and raise response quality across teams.”

“Software engineer at Expedera working at the intersection of deep learning compilers and neural processor hardware, focused on making customer models run efficiently across custom HW architectures. Particularly notable for building a zero-to-one multi-chip scheduler in a Python + C++ stack and for translating complex model optimization problems into customer-facing performance gains for hardware deployments, including autonomous driving use cases.”

“Frontend-focused candidate with React/TypeScript project experience spanning a senior design ADHD study app and an internship building ConfirmAddress.app. Stands out for combining role-based access/privacy thinking, education-regulation awareness, and hands-on debugging of login/state issues, with a strong emphasis on simple UX that supported real customer adoption.”

“Product/backend engineer from Revinate with experience in a startup-like SaaS environment, working on B2B tools for hotel managers. Stands out for hands-on performance optimization work that cut core service response times from roughly 800ms to about 300ms using Redis caching and database query improvements, alongside full-stack JavaScript/TypeScript and Python experience.”