We are seeking a skilled freelancer to develop an AI-driven sales pipeline and lead generation system. The ideal candidate will have experience in AI technologies and a strong understanding of sales processes. Responsibilities include designing and implementing AI solutions to enhance lead generation and sales conversion rates. The project requires an intermediate level of proficiency and is expected to last 1 to 3 months.

We want to develope an iphone app similar to our GoCanvas app that incorporates AI for job inspection reports. We will start with daily inspection reports and then create inspection and testing reports. We have dozens of existing reports that can be reduced to only a few with drop down options. I want field techs to take photos and dictate observations. AI should then draft a report to be saved in our Dropbox. I have attached one sample report. The main drawback to GoCanvas is once report is submitted for review, we are limited and no new sections or photos can be added. Also, some pages are very busy and some nearly blank, so appearance can be improved. Some basic construction knowledge is helpful.

We are looking for an experienced mobile app developer to complete a small AI integration task for an existing React Native or Flutter application. Scope of work: * Integrate an AI API (OpenAI, Gemini, Claude, or similar) into an existing mobile application. * Build a simple AI-powered feature based on our requirements. * Ensure the integration is fast, stable, and production-ready. * Deliver clean, well-structured, and documented code. This is a small one-time project. When applying, please include: * 5–10 live mobile apps you've worked on (App Store or Google Play links preferred) * Any AI-powered mobile apps you've built * Your role and contribution to each project * GitHub, portfolio, or LinkedIn profile (if available) Only apply if you have hands-on experience integrating AI into mobile applications.

We are seeking an experienced AI Data Mining and Lead Generation Team to help us build and scale two distinct sales verticals through advanced AI prospecting, automation, data enrichment, and lead qualification. This is not a simple list-building project. We are looking for professionals who understand how to leverage modern AI tools, automation platforms, CRM systems, and data intelligence to identify qualified prospects, verify contact information, and create systems that consistently generate meetings and sales opportunities. Our goal is simple: Vertical #1: Custom Apparel Sales Through The Tee Shirt Store, we provide custom apparel solutions for: Schools Sports teams Churches Nonprofits Small businesses Corporate organizations Fundraising campaigns Events and conferences We need qualified buyers actively looking for custom apparel, screen printing, embroidery, promotional products, and branded merchandise. Vertical #2: Youth Entrepreneurship Education Through Education With A Profit, we deliver entrepreneurship education programs designed to help youth develop business, leadership, financial literacy, and entrepreneurial skills. We need introductions and meetings with: Youth organizations Community organizations Workforce development programs Nonprofits serving youth Corporate community outreach departments Foundations and grant-funded programs What We Need You To Build The ideal candidate or team will: AI Lead Generation Systems Develop AI-powered lead sourcing processes Build automated prospect identification workflows Create lead scoring systems Implement contact verification procedures Use data enrichment tools to improve lead quality Reduce manual prospecting through automation Qualified Lead Acquisition For Custom Apparel: Identify decision-makers responsible for apparel purchasing Verify contact information Capture buying signals Prioritize high-intent prospects For Entrepreneurship Education: Identify educational leaders and program decision-makers Locate grant-funded and budget-approved opportunities Identify organizations actively seeking youth programs Build targeted outreach databases Automation & CRM Integration CRM setup and optimization Automated lead routing Follow-up automation Meeting scheduling integration Reporting dashboards Pipeline tracking AI Outreach Optimization Email personalization systems Prospect segmentation Multi-channel outreach workflows Lead nurturing sequences Appointment-setting automation

**Overview** We are a fast-growing SaaS company with a lean engineering team (~10 devs) utilizing a modern Python (FastAPI/Django) and Node.js backend, React frontend, and PostgreSQL stack. We have already deployed an initial multi-model agent stack—Claude Code, LiteLLM gateway, Git worktrees, and MCP integrations. We need an expert to run an intensive architecture review and optimization session for our current infrastructure. We are not looking for someone to build a full-time, weeks-long project from scratch. Instead, we need a seasoned engineer who has shipped this exact type of infrastructure end-to-end to audit our setup, identify architectural gaps, and guide our team on hardened implementation. This project must move fast. If your timeline is measured in weeks, please do not apply. We want someone who looks at this scope, jumps into a review session, and delivers actionable architectural guidance in days. This starts as a focused, urgent consultation. However, we expect ongoing advisory work—follow-ups, architecture adjustments, and enhancement reviews—as the AI tooling landscape shifts. For the right engineer, this will turn into a recurring relationship. We are completely open to a fixed price per milestone or an hourly structure. **What You Need to Have Actually Shipped and Can Review (Not Just Read About)** * **Full Agentic Coding Harnesses:** The entire loop: orchestrator → subagent → CI gate → merge loops. * **Isolation Layers:** Configured execution layers (such as E2B, Modal, or secure Docker runtimes) as isolated sandboxes for AI-generated code. * **Parallel Claude Code Sessions:** Managed multiple simultaneous subagents on scoped tasks via Git worktrees. * **Self-Hosted LiteLLM Gateways:** Routing to multiple models (Claude, GPT, Gemini, DeepSeek). * **MCP Server Infrastructure:** Connected file system, PostgreSQL, Atlassian, and Slack tool layers for active agents. * **Agent Framework Structures:** Used CLAUDE.md, COMMON\_MISTAKES.md, subagent role definitions, hook scripts, and settings.json. * **Human-in-the-Loop Orchestration:** Built Plan Mode or equivalent approval gates before agent execution. * **Multi-Agent Frameworks:** 7-agent feature factory patterns or frameworks like LangGraph, CrewAI, or Autogen. * **Durable Workflow Engines:** Applied Temporal, n8n, or similar tools for long-running agent workflow execution. * **Mechanical Quality Gates:** Treating CI green as the ultimate gate for agent output quality. \[[1](https://manveerc.substack.com/p/ai-agent-sandboxing-guide)\] **Our Current Stack (What you are reviewing)** * **Backend:** Python (FastAPI / Django) & Node.js (TypeScript) * **Frontend:** React (Next.js) * **Database & ORM:** PostgreSQL / Prisma / SQLAlchemy * **Infrastructure:** Docker Compose, AWS (ECS/EKS) * **CI/CD:** GitHub Actions / GitLab CI * **AI Layer:** Claude Code with shared `.claude/` directory, CLAUDE.md, and LiteLLM gateway in Docker * **MCP:** Atlassian (Jira/Confluence), custom PostgreSQL MCP server, Slack * **Workflow Automation:** Temporal / n8n * **QA Automation:** Playwright / Autonoma **Scope of Work (Review & Advisory Only)** 1. **Comprehensive Audit:** Audit our current agent harness and identify architectural gaps against a production-grade standard. 2. **Sandbox Strategy Consultation:** Review our environment strategy to ensure highly secure, isolated execution runtimes for agent code runs. 3. **Workflow Hardening Review:** Evaluate our parallel agent workflow setup (Git worktrees, subagent role configs, hook scripts, and settings lockdown). 4. **CI Pipeline Integration Strategy:** Advise on wiring our sandbox execution layer into the existing CI pipeline so agent-executed code runs in clean snapshots, not live infra. 5. **Architectural Runbook:** Deliver an optimization report / documented standard that our backend lead can easily own and execute going forward. **How to Apply** Skip the generic pitch. Show us something real to be considered: 1. A GitHub repo, architecture diagram, or Loom walkthrough of an agentic harness you have actually shipped. 2. Specific tools from our stack you have personally configured (E2B, LiteLLM, Claude Code, etc.). 3. One sentence explaining the hardest problem you solved to get full agent loops running reliably. 4. Your availability to conduct this high-impact architectural review session this week.

Seeking a LLM prompt engineer and solutions architect to develop AI medical note writing templates. The role involves creating structured templates for clinical documentation. Patient encounters will be turned into precise medical notes with good detail and reproducible note sections based on previous patient encounters. Also complete testing to ensure notes are compatible with my medical record system. The ideal candidate will have experience in medical documentation and AI solutions architecture.

Project Overview We are building an AI-powered voice receptionist agent for a dental practice client. The agent will handle inbound calls 24/7 — booking, rescheduling, and canceling appointments, answering FAQs, and escalating complex situations to a human. The voice layer is built in Retell.ai and the orchestration/automation flows run in n8n, with integration into a dental practice management systems. This is a hands-on build role, not consulting. You will design, configure, and iterate the agent working directly with our founding team. What You'll Build: Conversational voice flows for new and returning patients (booking, rescheduling, cancellations, FAQs, insurance questions, urgent/emergency triage) Clean escalation paths to human staff when the agent can't handle the call n8n workflows connecting the voice agent to the practice management API for real-time schedule reads/writes HIPAA-conscious configurations and tool choices throughout the stack Performance tracking and iterative prompt/flow improvements based on real call feedback Seeking an Expert Who: You've built multiple production voice agents, ideally in healthcare or dental, and can own the full stack from architecture to delivery. You think critically about latency, barge-in behavior, edge cases, and HIPAA compliance — not just happy-path flows. Requirements: Deep expertise in Retell.ai — prompt tuning, latency optimization, interruption/barge-in handling, LLM selection, and cost modeling Advanced n8n automation — complex branching logic, dynamic data handling, external API integrations, and error recovery Experience with dental or healthcare organizations — you understand how practices operate, what front desks actually deal with, and how to translate that into agent logic HIPAA awareness — you know which tools and configurations are appropriate for PHI workflows Track record of full-cycle delivery: scoping → build → pilot → iteration Nice to have: Dentrix Ascend integration, NexHealth, prior AI receptionist or appointment-booking agent for a clinic/practice. 📋 To Apply, Please Answer Have you built a production voice agent with Retell.ai? If yes, briefly describe it. What's your approach to managing Retell.ai per-minute costs on an inbound call agent? Have you worked with dental or healthcare clients before? What was the workflow? Paste a relevant n8n workflow screenshot or describe your most complex flow.

I'm an AI automation expert with a growing roster of clients, and I'm bringing on a skilled freelancer to help handle the smaller projects so I can keep up with demand. This isn't a new or one-off operation. I work with many clients already, and bring on new ones every week. I'm looking for someone reliable I can hand work to consistently, not just for a single project. You should be comfortable building AI automations independently and delivering clean, working solutions for client-facing work. To apply, please: - Send a short Loom introducing yourself - Share examples of your previous automation work I review every application personally, so a quick, genuine intro goes a long way. If we're a good fit, there's steady, ongoing work here.

Deliverable Requested from Developer Build a Google Workspace solution that: 1. Monitors incoming emails in slab-sewer@, rough@, and trim@ 2. Uses AI (Gemini, OpenAI, or similar) to classify severity and category 3. Automatically applies Gmail labels 4. Marks RED items as important 5. Runs automatically every few minutes 6. Requires no action from Project Coordinators Success Metric: A Project Coordinator can open their inbox and instantly identify which emails require immediate action versus which can wait until later in the day, without manually reading and sorting every message.

We are not looking for someone to create a single avatar. We are looking for a long-term creative partner to help build one of the world's most recognizable AI media brands. If you're excited about combining AI, storytelling, and positive global impact, we'd love to hear from you. Bonus experience: News media Animation Digital influencers Entertainment branding Intellectual property development To Apply Please include: Your portfolio of AI characters. Examples of consistent AI characters you've developed. The AI tools you use most often. Your process for maintaining character consistency across thousands of images and videos. Your favorite AI character you've created and why. A brief description of how you would design a globally trusted AI news host. Finalists will complete a paid concept assignment. Design one original AI news host for Global Positive News that includes: One hero portrait Three alternate expressions A short biography A sample script introducing the character Three example prompts showing how the character can be recreated consistently