We are looking for a senior Stripe fraud / payments risk expert to urgently audit and optimize our Stripe account. We are a high-volume e-commerce business currently dealing with a significant fraud/card-testing problem. Our payment success rate has dropped from approximately 85% to 35%, we have experienced 100,000+ Radar blocks, and our fraud dispute rate has recently increased to approximately 5%. We need someone who can identify exactly what is happening and help us stop fraudulent transactions without unnecessarily blocking legitimate customers. Scope of Work Audit our Stripe Radar and current fraud settings Analyze blocked transactions and determine how much is card testing vs. legitimate traffic Reduce our false-positive rate and improve legitimate payment authorization rates Configure and optimize Stripe Radar / Radar Pro Develop appropriate rules for normal, elevated, and highest-risk transactions Optimize 3D Secure / Adaptive 3DS Implement or recommend velocity rules, rate limiting, bot/card-testing protection, and other checkout protections Analyze issuer declines and payment failure reasons Help reduce our current fraud/dispute rate Review our existing fraudulent disputes and recommend the best strategy for recovering funds Advise on Visa/Mastercard dispute monitoring and pre-dispute tools such as RDR, Verifi, and Ethoca Create a longer-term fraud prevention strategy Ideal Candidate We are looking for someone with deep, hands-on experience, not a general Stripe developer. You should have experience with: Stripe Radar / Radar for Fraud Teams / Radar Pro Large-scale card-testing attacks E-commerce fraud prevention False-decline optimization Payment authorization optimization 3D Secure Chargebacks and fraudulent disputes Visa/Mastercard fraud monitoring programs High-volume Stripe accounts Experience working at Stripe, with former Stripe risk teams, or managing fraud for businesses processing 8–9 figures annually is a major plus. This is urgent. We would like someone who can review the account with us immediately, diagnose the problem, and provide actionable changes within the first 24–48 hours. When applying, please briefly describe a similar Stripe fraud/card-testing situation you have personally handled, the payment volume involved, and what you did to resolve it.

We run operations for a small financial-services firm and our team is buried under a stack of tools that don't talk to each other. We need a custom internal tool: a customer portal our clients and staff log into instead of juggling spreadsheets and half a dozen apps. First-phase scope: - A web application (Next.js or similar) with role-based access for admins, staff, and clients. - A Stripe billing integration that saves a card on file and runs autopay, plus ACH payment support. - A QuickBooks integration for nightly reconciliation so our books stay correct. - Light workflow automation and an API integration layer to wire up a few third-party services and replace a fragile Zapier setup that keeps breaking. - An admin dashboard and a client-facing dashboard that read live from our systems, not last week's export. A later phase may add an AI assistant, a chatbot over our own data, so staff can ask a question and get pointed to the right record. This is an ongoing project and we want a senior developer who can own the architecture end to end. Please share a couple of relevant portals or internal tools you've built.

About the Project I am launching a new career advisory company for women. The website design, content, and HTML are substantially complete. This is not a website build, redesign, custom software, or AI project. I need an experienced contractor to connect the systems behind the client experience into one reliable workflow: Website → Stripe payment and policy acceptance → client intake and secure file upload → Google Workspace storage → notifications and routing Scope Configure Stripe checkout, including required acceptance of Terms, Refund, and Privacy policies, with a retained record of who accepted which version and when Connect successful payment to the client intake form Configure secure document upload with no client account required Route submissions and files into Google Workspace with appropriate permissions and access controls Set up notifications and routing Deploy the existing HTML site and connect it to the workflow Test the full journey end to end, including likely failure points Provide clear documentation and a handoff a nontechnical founder can operate without a developer Tools Stripe, Google Workspace, an online intake form, a secure upload service, Vercel, and existing HTML, CSS, and JavaScript. I am open to alternatives when there is a clear reason, but I do not want unnecessary complexity or custom software where established tools will do the job. You Should Be U.S.-based, able to personally perform the work rather than subcontracting it, experienced with Stripe checkout and connecting forms to secure file upload and cloud storage, comfortable with permissions and responsible handling of customer information, and able to document your work clearly. You must also be willing to sign confidentiality, intellectual-property, and data-security agreements. Timing: Approximately 3 to 4 weeks Budget: Fixed-price, $5,000 to $8,000, paid by milestone Generic proposals that do not answer the screening questions will not be considered.

We're building multiple AI-powered SaaS products and MVPs using modern technologies. We're looking for an experienced Full Stack Developer to help build new features, fix bugs, improve performance, and ship products quickly. Most tasks are small and focused (typically 4–8 hours each), with the opportunity for long-term collaboration across multiple projects. What You'll Be Working On Typical tasks include: • Building new features with Next.js and NestJS • Working with Supabase (Auth, Database, RLS, Storage, Edge Functions) • Developing AI chat features using OpenAI or other LLM APIs • Integrating Stripe subscriptions and payment flows • Building REST APIs and backend services • Creating responsive UI with Tailwind CSS • Fixing bugs and improving application performance • Refactoring and improving existing code • Reviewing and improving AI-generated code from Cursor, Claude Code, Lovable, or similar tools • Helping launch SaaS products and MVPs quickly Engagement • Small tasks (typically 4–8 hours each) • Ongoing work across multiple projects • Flexible schedule • Async communication • Long-term opportunity for the right developer When Applying Please include: • Your best Next.js + Supabase project • A SaaS or MVP you've built • Your experience with Stripe and AI integrations • Your experience with Cursor, Claude Code, or similar AI tools • Your availability this week What We're Looking For Ideally, you: • Have strong experience with Next.js, NestJS, and TypeScript • Have solid experience with Supabase • Have built SaaS products or MVPs • Have experience integrating Stripe and AI APIs • Can work independently and solve problems efficiently • Write clean, maintainable, and scalable code • Are comfortable using AI coding tools • Communicate clearly and provide regular progress update

PROJECT OVERVIEW We are launching a bilingual Telehealth Dermatology practice in Puerto Rico. We are hiring a single expert developer or boutique agency for a turn-key project. You will handle brand identity, web design, and full-stack development from concept to live launch. We are only awarding this as a single, comprehensive fixed-price contract. ESSENTIAL REQUIREMENTS The patient-facing website and intake funnel must be fully bilingual in Spanish and English with a seamless toggle switch.The platform must use an upfront payment gateway via Stripe or Square as a strict gatekeeper. No patient data or charts should be generated until a payment successfully clears.Upon successful checkout, the platform must automatically sync all data directly into our EMR, DrChrono, via REST API and OAuth 2.0 with zero manual data entry. CORE DELIVERABLES Phase 1: Brand logo design, style guides, and responsive web wireframes. Phase 2: Bilingual patient intake questionnaire with a secure high-resolution photo upload module. Phase 3: Automated DrChrono EMR integration to create patient profiles, map allergies or medications, and upload photos to the clinical queue. Phase 4: Real-time calendar syncing and secure video visit automation utilizing DrChrono telehealth capabilities. Phase 5: Full HIPAA-compliant architecture with end-to-end data encryption.

We are looking for a full-stack developer to design and build the MVP for Midnight Riviera, a new platform focused on nightlife events and recording studio discovery and booking. This should be a coded, functional MVP, not just a landing page or mockup. The goal is to launch a clean, premium platform that can begin accepting recording studios and processing bookings while also promoting Midnight Riviera events. PROJECT SCOPE Homepage Premium, modern nightlife/music-focused design Mobile responsive Sections for upcoming events and featured recording studios Clear navigation between Events and Studios Recording Studio Marketplace Browse recording studios Individual studio profile pages Photos, description, location/area, amenities, equipment, pricing, and availability information Basic search/filter functionality Studio Onboarding Recording studios can apply to join Midnight Riviera Studio submits business/profile information, photos, pricing, etc. Admin can approve or reject studios Approved studio profiles can be published to the marketplace Booking System Customer selects a studio Customer chooses or requests a date/time Studio can accept or reject the booking request Customer can pay through Midnight Riviera Booking status and confirmation are recorded automatically Customer and studio receive appropriate booking notifications Payments Stripe integration Preferably Stripe Connect architecture so Midnight Riviera can collect a platform commission and studios can receive payouts Payment and booking records stored in the platform Basic refund/cancellation capability Events Upcoming events page Individual event pages Event images, descriptions, dates, locations, pricing, etc. Ticket purchase button For the MVP, ticketing can integrate with an external ticketing provider rather than building a custom QR/ticketing system Basic Admin Admin should be able to: Add/edit/remove events Review studio applications Approve/reject studios Manage studio listings View bookings View basic payment/booking information TECHNOLOGY We are open to recommendations, but a stack such as Next.js/React, Supabase, Stripe, and Vercel would be appropriate. IMPORTANT We want a real coded application with a clean codebase that can be expanded after the MVP. The developer must provide full ownership and handoff of: Source code GitHub repository Database Deployment Stripe integration All project credentials/accounts Documentation needed for another developer to continue development This MVP does NOT need: Custom event QR/ticketing infrastructure Advanced messaging Advanced analytics AI features Native mobile apps Complex recommendation algorithms Large-scale enterprise functionality The focus is a simple, polished and reliable first version. BUDGET Fixed-price budget: approximately $3,000. We are looking for someone who understands how to keep an MVP lean and can recommend practical solutions rather than overengineering the first version. TARGET TIMELINE Approximately 4 to 6 weeks. WHEN APPLYING Please include: Examples of marketplaces, booking platforms or similar applications you have built Your recommended technology stack Whether you have experience with Stripe Connect Your estimated timeline Confirmation that all source code and project assets will be fully transferred at completion A brief explanation of how you would approach the recording studio booking and payment flow

We run a production backend for an AI-powered platform that helps users identify scams over voice and text in real time. It is live and functional today, built by our current lead backend engineer. We are hiring a second senior engineer to work alongside the existing codebase: validating the architecture, closing out remaining features, and adding capacity so the project is not dependent on a single developer. Stack: Python, FastAPI, Firebase, Firestore, Google Cloud Platform, Cloud Run, Twilio Voice and SMS, Stripe, LLM API integration (Anthropic, OpenAI, or similar), speech to text / text to speech pipelines. What you will do: Review and validate the existing backend architecture and Firestore data model Help close out remaining features ahead of a pilot launch Improve reliability, security, and production readiness where needed Work as ongoing backend capacity going forward You should have: Senior-level Python and FastAPI experience in production Real production experience with Firebase, Firestore, and Cloud Run Experience inheriting and working within an existing codebase, not just building from scratch Twilio voice or SMS experience strongly preferred Experience with Stripe and LLM API integrations a plus Clear written English and some overlap with US Eastern Time To apply, answer this: Describe a time you inherited another developer's production codebase. What was your approach to understanding it, identifying issues, and improving it without disrupting the existing system? Please skip generic template proposals. Repository access and full technical scope provided after a signed NDA.

Job Description We are looking for an experienced AI/automation developer to build a reusable conversational agent that can book appointments, collect payments, and integrate with different third-party systems through APIs. The solution should not be limited to one industry. It should have a modular, API-first architecture so it can be configured for healthcare, beauty, consulting, home services, restaurants, professional services, and other appointment-based businesses. The agent should be capable of communicating with customers, checking real-time availability, booking or rescheduling appointments, collecting required customer details, processing payments securely, and sending confirmations and reminders. Core Features AI-powered conversational booking flow Check real-time staff, service, and location availability Book, reschedule, and cancel appointments Support multiple services, employees, locations, and time zones Collect customer information and custom booking questions Calculate service prices, deposits, taxes, and discounts Generate secure payment links or payment sessions Confirm payment status before finalizing appointments Send booking confirmations and reminders Handle common customer questions Escalate conversations to a human when required Maintain conversation, booking, and payment logs Admin configuration for business rules and integrations Integration Requirements The platform should support integration through REST APIs, webhooks, and reusable connectors. Initial integrations may include: Google Calendar and Microsoft Outlook Calendly or similar scheduling platforms Stripe, PayPal, Square, or other payment gateways CRM and ERP systems Custom booking platforms Email, SMS, WhatsApp, web chat, or voice systems Zapier, Make, or n8n where appropriate We understand that no solution can automatically integrate with every system without configuration. The goal is to create a standardized integration layer that makes adding new systems fast and manageable. Technical Expectations Secure and scalable backend architecture OpenAI, Claude, Gemini, or another suitable LLM Function calling/tool calling for reliable actions Structured workflows rather than relying only on free-form AI responses Authentication and role-based access API key and credential management Webhook handling and retry mechanisms Time-zone and daylight-saving support Idempotency to prevent duplicate bookings or payments Proper error handling and audit logs PCI-conscious payment implementation without storing raw card details Documentation for adding new integrations Deliverables Technical architecture and database design Working MVP of the AI booking and payment agent Calendar and payment integrations Reusable connector or adapter framework Admin configuration interface API and webhook documentation Testing and deployment Source code and setup instructions Ideal Candidate Strong experience with AI agents and LLM function calling Experience building appointment-booking systems Experience with Stripe or similar payment APIs Strong Node.js, Python, or equivalent backend experience Knowledge of webhooks, OAuth, REST APIs, and third-party integrations Experience with conversational workflows, chatbots, or voice agents Ability to design a reusable multi-tenant architecture Strong understanding of security and payment compliance Please include relevant examples, your recommended architecture, development timeline, estimated cost, and the integrations you recommend for the first MVP.

I am an emergency physician who has built a functioning clinical documentation web application called ED Scribe. The front end is already built and working well. This is not a request to redesign or rebuild the application. I am looking for an experienced healthcare/cloud security developer to build and deploy a small, secure backend that will allow ED Scribe to send clinical text to the OpenAI API in an architecture suitable for HIPAA-regulated use. I am specifically looking for someone with real experience deploying healthcare applications involving PHI, BAAs, HIPAA-eligible cloud infrastructure, secure API design, and OpenAI or similar LLM APIs. Please do not apply if your experience is primarily general web development without healthcare/HIPAA infrastructure experience. Current Architecture ED Scribe is a React/TypeScript application built using Lovable. Patient encounter working data currently stays in: React state browser localStorage There is intentionally no cloud patient database. Account/authentication/subscription information may exist in the application's backend, but patient encounters should remain completely separate from account data. Currently, two AI functions transmit clinical text: Generate ED Note Generate disposition documentation, including discharge instructions/admission handoff Those calls currently follow approximately: Browser → Supabase/Lovable Edge Function → Lovable AI Gateway → Google Gemini I want this clinical-data pathway removed. Desired Architecture The final clinical data pathway should be: ED Scribe browser ↓ Secure backend API controlled by me ↓ OpenAI API using my organization's BAA-covered API account ↓ Secure backend ↓ ED Scribe browser Generated clinical documentation should return to the browser and continue to be stored locally. Important design goal I do not want to create a cloud repository of patient encounters. The backend should function primarily as a secure, stateless processing layer. One request comes in, one OpenAI request is made, the generated documentation is returned, and the clinical request/response is not intentionally persisted by our infrastructure.Scope of Work 1. Recommend and configure HIPAA-capable hosting Recommend an appropriate platform such as AWS, Azure, or Google Cloud. The hosting environment must: support HIPAA workloads allow execution of an appropriate BAA use appropriate encryption securely manage secrets support access controls/IAM allow PHI-safe logging configuration provide HTTPS/TLS be maintainable by a small SaaS business Please explain your recommendation before deployment. I am looking for a relatively simple architecture, not unnecessary enterprise complexity. 2. Build the ED Scribe API Create a secure endpoint similar to: POST /api/generate-ed-note It should accept: generation type clinical summary random request identifier Supported generation types will initially include: ED note generation discharge instructions admission handoff The endpoint should validate inputs and reject unsupported request types. 3. Integrate OpenAI server-side OpenAI API calls must occur only from the backend. The OpenAI API key must never appear in: browser code React frontend client-side environment variables localStorage Git repository browser network responses Use server-side secret management. The OpenAI model should be configurable without changing application code. I intend to use an OpenAI organization/project covered by an executed BAA and appropriately provisioned for HIPAA-eligible API use. The backend should use an appropriate HIPAA-eligible OpenAI API endpoint/configuration. Where appropriate, requests should use: store: false The clinical workflow should be stateless. Do not use persistent conversations, threads, vector stores, files, web search, MCP, or other unnecessary services for patient encounters. 4. Prevent PHI logging This is a critical requirement. Clinical request and response contents should not appear in ordinary application logs. Do not log: patient summaries generated notes HPI MDM diagnoses discharge instructions admission handoffs names MRNs DOBs clinical narratives request bodies response bodies Operational logging may include appropriate metadata such as: timestamp random request ID response status latency model token usage generic/sanitized error category Raw provider errors should not be logged if they could echo PHI. Cloud-provider request/body logging must also be reviewed and configured appropriately. 5. Authentication and authorization The backend must not simply expose a public OpenAI proxy. Implement secure authentication so only authorized ED Scribe users can make generation requests. ED Scribe already has user registration/login and subscription functionality. The developer should integrate the secure backend with the existing authentication system where practical. The backend should be able to verify: authenticated user authorization to use ED Scribe Do not use patient information as part of authentication. Do not rely on CORS alone for security. 6. Standard API protections Implement appropriate: HTTPS/TLS authentication authorization input validation payload-size limits rate limiting CORS restrictions secure secret storage sanitized error messages server-side security controls dependency/security configuration Production errors must not expose stack traces or secrets. 7. Preserve the existing application This project should make minimal changes to the working ED Scribe front end. Do not redesign: user interface clinical workflow patient navigation note structure procedure workflow EKG workflow disposition workflow payment page registration system The current clinical prompts are important and should initially be transferred to the new OpenAI pathway as faithfully as possible. This project is primarily a transport/security/backend migration, not a clinical prompt redesign. 8. Remove the existing clinical AI pathway After the new backend is functioning, clinical text should no longer pass through: Lovable AI Lovable AI Gateway Google Gemini the existing Supabase/Lovable generate-ed-note Edge Function unapproved analytics or telemetry services There should be no fallback to the old AI pathway. If the approved backend is unavailable, ED Scribe should fail closed and keep the clinical information local. 9. Preserve local-first patient data architecture Do not move patient encounters into a cloud database. Patient working data should continue to remain in the browser unless transmission to OpenAI is necessary for the requested generation operation. Do not create: cloud patient histories saved encounter databases cloud note backups synchronized patient lists Account/subscription information and patient encounter information should remain separate data domains. Security / Data Flow Audit Required At completion, I want a written technical report answering: Exactly what clinical information leaves the browser? Which hostname/service receives it? Does any clinical text reach Lovable? Does any clinical text reach Supabase infrastructure? Does any clinical text reach Google/Gemini? Does any clinical text appear in application logs? Could clinical text appear in cloud-provider logs? Does any analytics/telemetry platform receive clinical data? Where is the OpenAI API key stored? Can the browser ever access the OpenAI API key? Is any clinical request/response intentionally stored server-side? What OpenAI endpoint/features are being used? How is the backend authenticated? How is authorization enforced? How are secrets managed? What services involved in processing/transmitting PHI require BAAs? Are there any remaining HIPAA/security issues you believe should be addressed before production use? I also want an architecture diagram of the final data flow. Deliverables At completion I should receive: deployed secure backend working ED Scribe → backend → OpenAI integration backend source code infrastructure/configuration documentation deployment instructions list of cloud services being used list of required BAAs/service agreements explanation of secret management authentication documentation logging configuration security/data-flow audit architecture diagram basic operational instructions instructions for rotating the OpenAI API key instructions for updating the OpenAI model estimated ongoing monthly infrastructure cost The infrastructure and accounts should ultimately be owned and controlled by me/my company, not permanently hosted inside the developer's personal accounts. Required Experience Strong preference will be given to applicants with demonstrated experience in several of the following: HIPAA-regulated healthcare software PHI handling Business Associate Agreements AWS/Azure/Google Cloud HIPAA architecture OpenAI API healthcare AI/LLM applications React/TypeScript API authentication IAM secure secret management secure logging SaaS security Stripe/Supabase familiarity healthcare cybersecurity HIPAA experience is much more important to me than fancy UI development. Important I am not asking a developer to certify that ED Scribe is legally "HIPAA compliant." I understand that compliance also involves contracts, policies, BAAs, organizational safeguards, risk assessments, and legal review. I am hiring you to build and document the technical architecture necessary to support HIPAA-regulated use and to identify remaining technical compliance issues. Screening Questions Please answer all of these when applying: Tell me about a healthcare application you have personally built or deployed that handled PHI. What was your role? Which cloud provider would you recommend for this project and why? Have you configured AWS, Azure, or Google Cloud specifically for HIPAA workloads and worked with BAAs? Have you integrated the OpenAI API or another major LLM into a healthcare application handling PHI? How would you prevent clinical request/response bodies from appearing in application or cloud-provider logs? How would you authenticate requests from the ED Scribe React application without exposing backend secrets? Would you maintain the existing localStorage patient architecture or recommend changing it? Why? Please briefly describe the architecture you would propose for this project. What would you expect the approximate ongoing infrastructure cost to be for a small initial user base? What do you estimate for project cost and completion time? Please begin your proposal with the words ED SCRIBE so I know you read the entire posting.

First things first: as the title suggests, compensation for this project is tied to the growth of the platform through new subscriber revenue. Compensation A. Deploy the completed platform from the GitHub repository to the production infrastructure and prepare it to go live for launch .
Compensation: $100 B. On-Call Developer
Provide occasional technical support after launch in the unlikely event the platform experiences issues. Responsibilities include responding to support tickets and resolving production-related problems.
Compensation: $250/month (PENDING!) C. Launch Success Bonus
Receive a $500 bonus once the platform reaches 50 paying subscribers (PENDING!) Current Project Status Most of the development work has already been completed. The application has been tested, and the finished codebase has been delivered and pushed to GitHub. Deploy the latest version to production. The current website (myfelipe.ai) is still running an older version of the platform. Deployment Plan Step 1 – Complete the items outlined in the attached Pre-Launch Checklist. And also expand the outdated 3 industries to as many industries that can benefit from our AI assistant. Step 2 – Obtain Validation to Stripe and access API keys. Step 3 – Deploy the latest code to Render/Vercel, configure the production environment, and verify all required variables (including NODE_ENV, Stripe webhook secrets, and other production settings). Step 4 – After deployment, perform a complete end-to-end test of every platform feature. Once everything has been verified, we start getting ready to go live, we have been planning a marketing campaign by activating a waitlist. Adding your name to the waitlist consist of a $99 payment, which Gateway via Stripe has already been created and tested. Launch Goal Our target launch date is July 24. Before launch, we plan to convert as many waitlist members as possible into early subscribers. Membership Pricing Please review myfelipe.ai to see the three current membership tiers. However, this is an outdated version and will have to be replaced with the attached pricing framework. (See link). We would like to expand our pricing options by offering: ● A month-to-month membership ● A discounted 1-year membership ● A heavily discounted 5-year membership ● A Lifetime Membership at a special introductory price Customers who join the waitlist by paying the $99 reservation fee will receive exclusive launch pricing unavailable to the general public. (access granted day of launch) Why Join Us? We’re building more than another AI application—we’re creating a platform designed to help small businesses become more efficient through practical AI automation. If you’re looking for an opportunity to help launch a real SaaS product with long-term growth potential and believe in building something meaningful, we’d love to have you on the team. https://docs.google.com/document/d/1-XKuFjdl1kUu8xTu_paAW3ejRT2icHTcVTEMBB2G7pA/edit?usp=drivesdk