Vetted Flask Professionals

“Full-stack product engineer who has shipped AI-powered job board moderation and validation features end to end across React/TypeScript, serverless backends, and Postgres. Stands out for combining UX polish, LLM-backed workflow design, and reusable async infrastructure patterns to improve reliability, speed of delivery, and user participation.”

“Lead Unity Developer with mobile game shipping experience since 2016 (iOS/Android) and a portfolio of multiple Unity games built entirely solo (benfont.com). Uses Codex daily to speed up development and recently leveraged it to debug Unity lightmapping issues in a newer engine version.”

Jaiden Kettleson

Screened ReferencesStrong rec.

Entry-Level Full-Stack & AI Engineer specializing in chatbots and web apps

1y exp

“Data Science honors graduate (Maryville University) who has built Python/SQL backends and a capstone website handling sensitive user data. Emphasizes secure data handling (password encryption, secure database updates) and uses Git/GitHub Pages with CI/CD-style practices for managing and deploying changes.”

“Software QA tester with manual + automation experience (Jira, Figma) looking to transition into console game testing; brings long-term multi-console player perspective (Nintendo/PlayStation/Xbox) and a structured, risk-based approach to triage and release readiness. Has used AI assistants to rapidly generate large sets of API test cases under tight deadlines.”

Muhammad Murtaza Murtaza

Screened

Mid-level Machine Learning Engineer specializing in NLP, Computer Vision & Predictive Analytics

Islamabad, Pakistan5y exp

“Built a production LLM fine-tuning pipeline for domain-specific code generation at Pigeonbyte Technologies, including automated collection and rigorous quality filtering of 10M+ code samples (AST validation, sandbox execution/testing, deduplication, drift monitoring, and human-in-the-loop review). Also implemented end-to-end ML orchestration in Apache Airflow with data quality gates, dataset versioning in S3, benchmarking, and automated model promotion, and has a reliability-first approach to agent/workflow design.”

“Built production-style backend and AI systems across internship and project work, including a real-time sports platform backend and a Smart Email Assistant using GPT-4. Stands out for combining classic backend performance engineering with practical LLM workflow design, including measurable latency improvements, high uptime, and debugging of non-deterministic model behavior.”

“Hands-on technical/product-facing engineer with experience operationalizing LLM/agentic workflows and debugging them in real time using logs, traces, and metrics. Also supports go-to-market by running developer-focused live coding demos and partnering with sales on discovery and integration/maintainability concerns through clear technical documentation.”

“Full-stack engineer and Scrum Master who led a major monolith-to-microservices migration, including a micro-frontend Angular architecture using Native Federation and staged integration into the legacy app. Also built a React + TypeScript “Business Risk” product featuring a metadata-driven dynamic dashboard/forms layer backed by Spring Boot + GraphQL, with strong QA practices (unit/integration/E2E via Cypress), CI/CD, and feature toggles.”

Jason Burleigh

Screened

Senior Solutions & Systems Integration Engineer specializing in API automation and operational platforms

Los Angeles, CA11y exp

“Customer-facing LLM/agent workflow specialist who repeatedly takes unstable prototypes to production by enforcing strict I/O contracts, validation/guardrails, and reliability patterns (logging, retries, timeouts, monitoring). Strong in real-time troubleshooting using logs and payload inspection, and known for live demos/workshops that teach teams to self-debug. Partners closely with sales by building POCs in customer environments to unblock trials and drive faster deal closure and adoption.”

“Built and deployed an LLM-powered automation pipeline that ingests voice and documents, transcribes/extracts key information into structured data, and routes it through backend workflows using Python/FastAPI. Uses n8n to orchestrate multi-step AI processes with validation, retries, and monitoring, and iterates with stakeholders via rapid demos to refine changing requirements.”

“Application security engineer/advisor with hands-on experience securing AWS-based, containerized services and embedding SAST/DAST/SCA and container scanning into GitHub/GitLab CI/CD. Drove measurable outcomes (50% faster vuln triage, 40% fewer misconfigs) and has deep operational troubleshooting experience in Kubernetes (agent failures due to CPU throttling/network policies), plus pragmatic strategies to reduce developer friction and handle API rate limits.”

“Backend/ML engineer with deep fintech and marketplace experience: built a real-time financial analytics + algorithmic trading platform (Python/Postgres/Kafka/Redis) and drove major DB performance wins (10x faster analytics; sub-10ms response consistency). Also shipped an end-to-end ML recruitment matching platform (scraping/ETL/modeling/Django deployment) with reported 92% matching accuracy, and emphasizes production reliability via monitoring, blue-green deploys, and robust workflow error handling.”

ABHIGNAN YANGANGARI

Screened

Junior Full-Stack Software Engineer specializing in Java/Spring Boot and React

Hyderabad, India1y exp

“Full-stack engineer who built a lost-and-found pet management platform (React + Node/Express + SQL) with a focus on scalability (stateless JWT auth, modular REST APIs, cloud-based image handling) and performance (Artillery load testing, Chrome DevTools, query/index tuning). Also demonstrates systems-thinking around low-latency real-time voice pipelines integrating WebSockets, ASR, LLMs, and audio output, and has experience translating founder input into shippable product via rapid prototyping.”

“AI/ML practitioner with production experience building a RAG-powered contextual customer support agent, optimizing for low latency using vector databases and smaller LLMs. Also deployed a fraud detection model on Kubernetes with auto-scaling for heavy transactional loads, and improved chatbot accuracy by 15% through metric-driven testing and evaluation. Partners with Marketing on personalization/recommendation initiatives with measurable outcomes tied to customer feedback.”

“QA/automation tester with experience across Cypress/Playwright/Cucumber and API testing who helped a large team with limited QA bandwidth by automating a previously manual Excel verification workflow using pandas. Reported a critical data-leakage defect and found ~40 issues during an old-to-new UI migration, collaborating regularly with developers/designers to improve product quality.”

Aldrin Azucena

Screened

Mid-level Full-Stack Software Developer specializing in web apps, CI/CD, and cloud infrastructure

Lethbridge, Alberta, Canada4y exp

“Frontend engineer (~4 years) who led an admin dashboard for potato farmers end-to-end, integrating real-time and historical weather data to drive disease-severity predictions. Built scientifically validated calculation pipelines (FAO Penman-Monteith, late blight models), rigorous Cypress/unit testing, and print/PDF-ready reporting, while optimizing performance and API load with debouncing, caching, and feature-flagged rollouts.”

Mohammed Elwaei

Screened

Junior Software Engineer specializing in systems, compilers, and AI research

Tampa, FL2y exp

“Engineering student with hands-on robotics and simulation experience: led an Arduino line-following “Batmobile” robot project used as a K–12 teaching tool and won best design in a 100+ student section. Also implemented SARSA reinforcement learning for a 16-DOF robotic hand in MuJoCo, optimizing the state representation to train efficiently on a CPU, and brings strong cloud/container skills (Docker, Kubernetes, AWS certs).”

“Built a Smart Resume Screening tool with a React frontend and a Python backend, owning most backend architecture and delivery. Implemented FastAPI endpoints for file upload and NLP/ML inference, created the end-to-end resume classification pipeline, logged predictions to a database for accuracy tracking, and deployed a Dockerized service optimized for low-latency, concurrent processing.”

“Early-career full-stack engineer who has not yet shipped a professional customer-facing product but has built sophisticated AI-driven systems in personal/academic work, including a multi-tenant AI knowledge base (async ingestion, pgvector semantic search, SSE real-time updates, knowledge graphs) and an AI-powered code review assistant designed to process thousands of jobs via Redis/BullMQ.”