I am working on a system using AI to review and respond on Google Drive (Shared Drive) folders of PDF's. Using Gemini as a POC I get responses that sometimes reach outside of my specified folders of content, but sometimes, some PDF files are ignored too. Also, when the response to a prompt come back, the sources are linked. However, the links only bring up the first page of the PDF file wherein the linked source material is, AND NOT THE pdf PAGE of the specific info. I need to have the AI (Gemini, Grok, etc.,) be used to query just.... but all, of the PDF files, within a set of folders in Google Drive (Shared Drive), and to respond with linked content. Said links must open to the PDF PAGE, not just the PDF which houses the specific info. In short, I think I need a viewer, but someone who has experience working with AI and PDF's will likely know the issue I am running into. In the end my system will have a UI attached, so there is a lot of possible side work on this project. First I need to build a better POC. For instance, if I open ONE of the PDF files in Google Drive, I can prompt on that file, and the correct PDF page does come up in the viewer, (While no other files are considered for the queried content.) But when I give Gemini many source PDF's or a folder of PDF's, the links only go to the first page pf the PDF with the information used as the sourcwe.

We are seeking a skilled GenAI engineer to work with our client in a remote or Chicago-based capacity. The ideal candidate will have experience in developing and implementing AI solutions, with a strong understanding of machine learning and data analysis. Responsibilities include designing AI models, integrating AI into existing systems, and collaborating with cross-functional teams to enhance AI capabilities. If you have a passion for AI and a proven track record in delivering innovative solutions, we would love to hear from you.

## Project Overview I am seeking an experienced Senior AI Systems Architect / Full-Stack Engineer to evaluate and potentially lead the technical architecture of a new enterprise software platform currently under development. At this stage, I am not looking for someone to simply write code. I am looking for an experienced technical professional capable of evaluating architecture, recommending technologies, and helping define the engineering roadmap for Version 1. The project involves the integration of artificial intelligence, enterprise software architecture, workflow automation, secure data management, API integrations, and cloud-based application design. Because the project contains proprietary intellectual property, detailed information will not be disclosed during the initial interview process. Candidates selected to move forward will be asked to execute a Non-Disclosure Agreement before reviewing project documentation. ## Initial Objectives • Review the existing project at a high level. • Evaluate technical feasibility. • Recommend the most appropriate technology stack. • Design the production architecture. • Develop an implementation roadmap. • If mutually agreed, continue as the lead software architect for Version 1. ## Required Experience Applicants should have significant experience with: • Enterprise software architecture • Artificial Intelligence integration • API development and integration • Full-stack application development • Cloud architecture and deployment • Database design • Authentication and application security Excellent communication skills are important. I am looking for someone who enjoys solving complex architectural challenges and who is interested in building something from the ground up. ## Please Include 1. A brief summary of your architecture experience. 2. Examples of enterprise software systems you have helped design. 3. AI-related experience. 4. Your preferred technology stack. 5. Why this opportunity interests you. The initial engagement is intended as an architectural evaluation. A longer-term relationship may develop if there is a strong mutual fit.

Build an AI Marketing Operating System for Local Business I am an orthodontist building an internal AI platform for my practice. This is NOT a website project. The platform should: * Continuously monitor public internet sources for local conversations related to orthodontics. * Use AI to determine whether a conversation is worth engaging. * Generate suggested responses in our brand voice. * Never publish automatically. * Present every suggestion in an approval dashboard where I can Approve, Edit, or Reject. * Generate blog posts, Google Business Profile posts, newsletters, Instagram captions, FAQs, and YouTube scripts. * Track analytics and improve recommendations over time. Technologies preferred: * OpenAI API * Make.com or n8n * React / Next.js * Supabase * Airtable (acceptable for MVP) * PostgreSQL * Docker Applicants should have experience with: * AI agents * Human-in-the-loop workflows * LLM integrations * Automation * Dashboard development

Rebuild a travel agency SaaS platform from a working no-code prototype to Next.js + Supabase. Features include Notion-style CRM, AI proposal builder (Claude API), client portal, commission tracking, Stripe billing, and Duffel flights API. Row-level security required. Fixed price project. Full working prototype provided as reference.

Title: Technical Delivery Lead / Orchestrator — AI & Automation Projects (Ongoing, Part-Time) Description: We're looking for a technically strong delivery lead to orchestrate AI and automation builds — not to do the hands-on coding (a dedicated dev team handles that), but to own the layer above it: scoping client needs, translating them into clear build plans, directing the dev team, and quality-checking what they ship. You'd be our technical point person on projects — comfortable on a call with a client or partner one minute, and reviewing the dev team's architecture the next. We need someone who can tell good work from bad, push back when something's off, and keep projects moving without being micromanaged. This is an ongoing, flexible, part-time role across a steady pipeline of work (marketing automation, agentic AI workflows, web/app builds). You'd start on one project to prove fit, then expand from there. Must-haves: - Strong technical background — you've built real things (read code, architect a solution, judge a dev team's work), with hands-on exposure to AI agents / automation (n8n, LangChain/LangGraph, or similar) - Client-facing polish — represent us professionally to clients and partners - Orchestration experience — you've scoped work and directed developers/teams, not just built it yourself - Based on the US West Coast — reliable overlap with both our team and an offshore dev team To apply, please include: To apply, just a few sentences on each: 1. One project where you scoped a client's need, directed a dev team, and delivered — what was yours vs. the team's 2. A line on your technical depth (something you've architected or built) and a line on client-facing work you've done 3. Your quick take: a client wants an "autonomous marketing system" live in 30 days — what's the first thing you'd want to know, and the most common reason these underdeliver? Keep it short — we're after sharp thinking, not a polished pitch. Individuals only — not agencies.

I am looking for a developer or agency to build a web platform called First Responder Academy. The goal is to create the most comprehensive AI-powered training platform for firefighters, EMTs, and paramedics. The platform will initially focus on: 1. Firefighter Oral Board Preparation 2. EMT NREMT Preparation 3. Paramedic NREMT Preparation 4. Firefighter I Certification Preparation 5. Firefighter II Certification Preparation Core Features Required: * User accounts and login system * Membership and subscription management * AI-powered training simulator * Progress tracking * User dashboard * Mobile-friendly design * Modern, professional interface * Ability to scale over time AI Training Features: The AI should be able to: * Conduct firefighter oral board interviews * Score responses * Provide detailed feedback * Generate EMT and paramedic scenarios * Generate Firefighter I and II questions * Create multiple-choice exams * Provide remediation and study recommendations * Increase or decrease difficulty based on performance Knowledge Base Features: The system should allow: * Uploading NREMT skill sheets * Uploading EMS protocols * Uploading Firefighter I and II standards * Uploading department-specific hiring packets * Uploading study guides and training documents The AI should reference uploaded materials when generating questions and grading answers. EMS Features: * EMT training mode * Paramedic training mode * NREMT-style testing * Practical scenario evaluations * Protocol-based learning * Trauma and medical assessment training * Airway management training * Cardiology training Cardiology Module: A major future feature will be ECG interpretation. Requirements: * ECG image library * Random ECG presentation * Student interpretation * AI grading and feedback * Rhythm recognition training * Treatment decision evaluation Firefighter Features: * Firefighter Oral Board Simulator * Firefighter I Exam Preparation * Firefighter II Exam Preparation * NFPA / IFSAC-based content * Scenario-based learning * Multiple-choice testing * Leadership and decision-making exercises Department-Specific Training: The platform should eventually allow users to: * Upload local EMS protocols * Upload department hiring packets * Upload mission statements and values * Receive customized training based on those documents Progress Tracking: The platform should track: * User scores * Weak areas * Practice history * Completion rates * Recommended study topics * Improvement over time Admin Features: * Upload and manage training content * Upload and manage protocol documents * Upload and manage ECG images * Create and edit question banks * View user analytics * Manage subscriptions Technology Preferences: * Modern scalable architecture * AI integration using OpenAI API * Secure user authentication * Cloud-hosted * Responsive design * Easy content management Design Style: * Professional * Modern * Clean * Fire and EMS themed * Dark mode preferred * Red, black, gray, and white color palette Important: I am looking to build an MVP first, not every feature immediately. Phase 1 priorities: 1. User accounts 2. AI training simulator 3. Oral board preparation 4. EMT preparation 5. Paramedic preparation 6. Firefighter I and II preparation 7. Progress tracking 8. Membership system Future phases can include ECG image testing, advanced protocol integration, department-specific customization, and additional first responder training programs. Please provide: * Estimated timeline * Estimated cost * Recommended technology stack * Examples of similar projects * Suggestions for MVP development

We are a medically backed, pre-seed healthtech platform preparing for an immediate enterprise pilot deployment. Our core user interface, interactive data features, and content architecture are functionally built utilizing modern AI-assisted development tools. We are seeking a senior, hands-on engineer with specific healthtech deployment experience to serve as our Execution Contractor for an immediate hardening sprint. You will own the backend security architecture, external cloud infrastructure configuration, and technical compliance validation required to transition our high-fidelity MVP into a secure production environment. What You’ll Do Harden Backend Security: Transition frontend route guards into strict, server-side authentication and authorization boundaries across all data-access paths. Architect Secure Infrastructure: Migrate core data architectures out of staging environments and securely provision an external, HIPAA-compliant cloud database tier. Manage Vendor & Compliance Workflows: Audit our technical vendor stack to securely embed enterprise API protocols, ensuring strict data handling and compliance alignment across all integrated platforms. Validate & Sign-Off: Run edge-case testing and performance audits to completely secure data handling pipelines, delivering a technical go/no-go sign-off for our upcoming pilot cohort. The Technical Stack Frontend: React 18+, TypeScript Backend: Node.js, Express.js Database/ORM: PostgreSQL via Drizzle ORM Environment/Tooling: WebSockets, Enterprise AI APIs, Secure Cloud Infrastructure (AWS / Supabase) Who You Are A seasoned full-stack or backend engineer with a proven track record of successfully deploying applications into live clinical, medical, or heavily regulated environments. Deeply knowledgeable in server-side encryption, data pseudonymization, and secure cloud networking. Highly comfortable inheriting, auditing, and optimizing architectures built alongside AI-assisted development workflows. An execution-focused builder who thrives in high-velocity sprints and values absolute production discipline. To Apply: Please submit your proposal directly through Upwork with a brief summary of your healthtech deployment experience, specifically highlighting your experience with secure data pipelines, PostgreSQL, and HIPAA configurations.

I’m looking for an AI Engineer to help build an automated red-teaming product based on open-source models. This is a short-term, hands-on project for around 2 months, with an expected commitment of about 20 hours per week. The goal is to build a specialized red-teaming engine that can generate adversarial prompts across different risk domains, severity levels, and attack strategies — then automatically run those prompts against target AI models to identify bad cases, failure patterns, and safety gaps. 🔍 What you’ll work on Build red-teaming systems on top of open-source LLMs, including fine-tuning, prompt optimization, evaluation pipelines, and model orchestration. Design automated prompt generation workflows across risk domains such as self-harm, hate, violence, sexual safety, misinformation, fraud, cyber, and other high-risk areas. Generate prompts across different harm levels, from benign edge cases to policy-borderline and clearly unsafe scenarios, while maintaining structured taxonomies and evaluation criteria. Run automated tests against target models such as Gemma, Llama, Qwen, or other open-source / closed-source models to surface jailbreak patterns, over-refusal, under-refusal, and policy inconsistencies. Build feedback loops that turn model failures into stronger red-team prompts, improved eval sets, remediation recommendations, and continuous safety testing. 🧠 What I’m looking for Hands-on experience with open-source LLMs, fine-tuning, LoRA / QLoRA, RAG, model evaluation, and LLM inference pipelines. Familiarity with AI safety, red teaming, adversarial prompting, jailbreaks, safety evals, or trust & safety systems. Ability to build end-to-end systems, including data pipelines, model serving, eval harnesses, scoring, dashboards, and automation workflows. Bonus if you’ve worked on model safety, content moderation, policy evaluation, agentic testing, or automated eval infrastructure. ⏳ Project setup Duration: around 2 months Time commitment: about 20 hours per week Format: flexible / remote-friendly Stage: early-stage build, from 0 to 1 🚀 Why this is interesting This is not about manually writing red-team prompts one by one. The goal is to build a scalable system that can continuously generate, test, categorize, and learn from model failures — helping teams understand where AI models break, why they break, and how to improve them. If you enjoy working with open-source models, AI safety, red teaming, and fast 0-to-1 product building, I’d love to chat. Feel free to DM me if this sounds like you, or if you know someone who might be a good fit.

We are looking for an experienced AI automation developer to build a private executive assistant named Jarvis for a business owner named Vince. Jarvis must operate as a professional, respectful, fast-moving executive assistant. The assistant will communicate with Vince through iMessage, access his Google Calendar, remember important information, send meeting reminders, and maintain local files/data on an office iMac. This is not a basic chatbot. We need a working AI assistant that can hold real conversations, remember context, anticipate needs, and protect Vince’s time. Core Requirements The assistant must: Communicate with Vince through iMessage on macOS. Store all data, memory, and files locally on the office iMac. Access Vince’s personal Google Calendar. Send Vince a message 20 minutes before meetings. Remember meeting times, preferences, important facts, and prior conversations. Use context from previous messages and stored memory. Start conversations professionally with: “Hello Sir. What do you need today sir.” Maintain a direct, respectful, professional tone. Avoid fluff, long explanations, repetition, and unnecessary questions. Understand that Vince has zero tolerance for wasted time. Validate Vince’s instructions and respond with useful answers quickly. Ask onboarding questions at first launch to learn Vince’s occupation, goals, priorities, communication preferences, daily routines, and assistant expectations. Be built in a way that can expand later into email, task management, document handling, and proactive reminders. Important Personality / Communication Rules Jarvis must be designed around Vince’s communication style: Direct. No fluff. No jargon. Lead with the answer. Never ask for information Vince has already provided. Protect his time, brand, relationships, and workflow. Jarvis should function as an executive personal assistant whose purpose is to remember everything so Vince does not have to repeat himself. Technical Scope The developer should be comfortable with: macOS automation. iMessage / Messages.app integration. Google Calendar API. Local file storage and local memory architecture. AI agent frameworks. Cron jobs or scheduler-based reminders. Secure credential handling. Local database or file-based memory. Python, Node.js, or similar automation stack. Optional: BlueBubbles, AppleScript, Shortcuts, SQLite, vector database, local LLM tools, OpenAI API, Claude API, or similar. There is already a macOS/iMessage path available using CLI-based message tooling, but we are open to the developer recommending the best reliable implementation. Existing iMessage automation concepts include sending, reading, and watching message history through macOS Messages.app tooling. Deliverables We need the developer to provide: Working Jarvis assistant installed on the office iMac. iMessage communication with Vince. Google Calendar integration. Automatic 20-minute meeting reminders by text. Local memory system. Local file/data storage structure. First-run onboarding question flow. Prompt/personality system for Jarvis. Basic admin documentation showing how to restart, update, and maintain the assistant. Security notes for credentials, permissions, and local storage. Testing checklist proving iMessage, memory, reminders, and calendar sync work. First-Run Intro Flow Jarvis should text Vince an introductory message and ask important setup questions such as: What is your primary occupation? What are your top business priorities right now? What meetings or events should I always remind you about? Who are your key contacts? What should I never interrupt you for? What should I always notify you about? What tone do you prefer from me? What daily reminders would make your life easier? What are your current goals for the next 30, 60, and 90 days? Ideal Candidate The ideal freelancer has built AI agents, personal assistants, calendar bots, local automation tools, or macOS/iMessage workflows before. We want someone practical who can build a reliable working system, not just create a demo. Please include: Similar AI assistant or automation projects you have built. Your recommended tech stack. How you would connect iMessage. How you would handle local memory. How you would secure calendar credentials. Estimated timeline. What you need from us to start.