Vetted Prompt Engineering Professionals

Richa Chanpuriya

Screened

Mid-level Backend/Agentic AI Engineer specializing in GenAI automation and RAG systems

Remote, India3y exp

“Built and shipped a production AI-driven privacy automation system that autonomously navigates data broker sites to submit opt-out/data deletion requests end-to-end, including robust CAPTCHA detection/solving (e.g., reCAPTCHA/hCaptcha/Cloudflare) via 2Captcha. Experienced in orchestrating stateful LLM agent workflows with LangGraph and hardening them for production with strict state management, retries/fallbacks, validation layers, and database-backed observability/audit logs, collaborating closely with legal/compliance stakeholders.”

Manas Kumar Sherla

Screened

Junior Machine Learning Engineer specializing in NLP and LLM-based clinical AI

Charleston, IL2y exp

“Built a production automated resume matching system using Python, FAISS vector search, and Selenium-based job scraping, including mitigation for IP blocking and heterogeneous site structures. Also develops LLM/RAG applications with LangChain, using Pydantic-guardrailed structured outputs and LLM-as-a-judge evaluation (including a project focused on tone/semantics for a 3D avatar’s emotional responses).”

Nikunj Baraiya

Screened

Mid-level Unity Game Developer specializing in multiplayer and AI-driven gameplay

Bhavnagar, India4y exp

“Unity developer who has shipped mobile and Meta Quest experiences, including a real-time audio collaboration app using Unity + Photon Fusion. Demonstrates end-to-end gameplay ownership plus production LLM integration (Firebase-delivered quests) with measurable latency/cost improvements and a disciplined A/B + analytics-driven iteration loop; also experienced debugging live multiplayer issues (desyncs, NAT failures) with tools like Wireshark.”

“Early-career/learning-stage candidate focused on LLM systems; has not yet built or deployed production AI applications but is actively learning orchestration (Microsoft Semantic Kernel) and core patterns like RAG, embeddings, and model selection based on business requirements.”

“Hands-on builder who has shipped multiple self-directed Python automations, including a PySide6 desktop app that uses LLMs for job search and resume matching, plus AWS-hosted notification workflows and Chromium-based browser automation. Particularly interesting for roles involving AI integrations, automation, and reliability work because they speak concretely about schema drift, hallucination mitigation, observability, threading, and flaky auth/session handling.”

Bishara Bishara

Screened

Entry-Level Software Engineer specializing in AI/ML pipelines

1y exp

“Built a production LLM-powered interview-prep app that ingests job postings and generates tailored preparation plans. Iterated from a single generalist LLM to a multi-LLM pipeline and used RAG to ground the final chat assistant on locally stored intermediate outputs; has also experimented with n8n vs Python-coded pipelines for orchestration.”

Mohammad Al-Hudban

Screened

Intern AI Engineer & Data Scientist specializing in GenAI, LLMs, and RAG

Leoben, Austria0y exp

“Currently working at CBS Lab in Austria, where they implemented/replicated the "Open World Grasping" research pipeline end-to-end. Built a ROS-based RGB-D perception-to-action system using SAM 2.1 segmentation and MoveIt motion planning to generate grasp poses and execute pick-and-place/sorting with a robotic arm.”

Kumar Manik

Screened

Intern AI Engineer specializing in LLMs, MLOps, and RAG systems

0y exp

“Built and shipped a production-grade RAG-powered news summarization and Q&A product, tackling real-world issues like retrieval drift, hallucinations, latency, and autoscaling deployment (Docker + FastAPI + Streamlit Cloud). Experienced in end-to-end ML/LLM workflow automation using Airflow, Kubeflow Pipelines, and MLflow, and has demonstrated business impact (40% inference precision improvement) through close collaboration with non-technical stakeholders at Evoastra Ventures.”

Rutvi Rathod

Screened

Junior Full-Stack Software Engineer specializing in AI and web applications

San Jose, CA1y exp

“LLM/AI backend engineer with hands-on experience taking customer LLM prototypes into production using FastAPI, containerization, CI/CD, and OpenTelemetry-based observability. Demonstrated measurable impact by cutting LLM costs ~40% and reducing workflow errors ~50% through schema-enforced outputs, better tool definitions, retries, and prompt/model optimization; also supports pre-sales via technical discovery and rapid integration demos.”

Mark Lorence Collado

Screened

Junior Graphic Designer & Social Media VA specializing in AI-assisted content and ads

Bongabon, Philippines2y exp

“Marketing creative designer producing polished static ads and lightweight social videos, primarily using Photoshop, Canva, and CapCut (no Figma yet). Emphasizes scalable template-based workflows for high-volume output, strong visual hierarchy for clarity, and remote async collaboration with rapid feedback cycles; shared portfolio on Behance.”

“Built and deployed a production RAG chatbot using a vector database + LangChain-orchestrated pipeline, focusing on grounded, context-aware responses. Demonstrates practical trade-off thinking (retrieval quality vs latency/cost), hallucination control, and iterative improvement through logging, manual review, and stakeholder feedback loops.”

Joe Francia

Screened

“Gameplay engineer with Unity/C# experience across AR and multiplayer, including building a custom dynamic navigation system for an AR "floating island" game (with profiling-driven optimization from A* to Markov-chain movement). Also designed an LLM-assisted conversation system for Sims-like gameplay that constrained choices for reliability and low latency, and shipped Photon Quantum multiplayer features with practical desync/prediction fixes.”