## 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.

Need someone to build me an CFO ai agent that can analyze monthly P&Ls and Balance Sheets from multiple different businesses within a franchised system. The financials will be in PDF format. Also need the ai agent to transfer funds from checking accounts to PayPal every week (I currently do this manually so it's setup, just want it automated)

Want someone to go over our Retell prompts / get best practices, must be a retell partnered agency. Please share previous projects and the name of your business on retells site.

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.

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.

I’m running a real estate investment platform called ToInvested.com. The project is about 90% finished, and most of the code was built with Claude together with another engineer. Now I need a senior engineer to step in, review the full product carefully, test every major workflow, and help verify that everything is working correctly before it goes live. This is not just a “write more code” role. I need someone who can look at the platform like a real product, find hidden bugs, catch weak logic, test edge cases, review the AI-generated code, and tell me honestly what is ready and what still needs fixing. Because this is a real estate investment platform, accuracy and trust matter a lot. Users may rely on property data, investment logic, calculations, and AI-driven insights, so even small issues can create a serious problem later. The ideal person has strong full-stack experience, understands AI-assisted development, and has a good testing mindset. Real estate tech experience would be a big plus, especially with property platforms, investment tools, marketplaces, mortgage systems, or financial workflows. My main goal is simple: I want someone to break the project before real users do. If you’re the kind of engineer who can take a nearly finished product, test it deeply, clean up weak areas, and help make it production-ready, I’d be happy to talk.

Role Overview You are the Executive AI Enablement Lead at AIVC, the person whose job is to make the executives at AIVC’s client businesses true power users of Claude, Cowork, and code- and agent-driven workflows. AIVC partners with operator businesses to drive AI-led EBITDA growth, and part of that work is bringing each company’s most senior leaders up the AI curve. You’re the person who personally designs and runs that path on every engagement: assessing where a given client executive is today; curating the right materials, videos, and course content; running 1:1 coaching; building executive playbooks; and acting as their daily operator-in-the-loop until the new workflows stick. The first concrete instance is already lined up, a named client managing partner has explicitly asked for the fastest path to becoming a power user of Claude, Cowork, and Claude Code / Skills. From there you scale: same treatment to additional client executives across the portfolio, then a documented set of executive-grade playbooks and patterns that compound across every future engagement. You are bias-toward-results – a win is the client executive’s calendar-week looking different, not a beautifully written rubric nobody uses. What You’ll Own (Outcomes) • Within 30 days of pairing with the first client managing partner, they have a working daily routine in Claude, Cowork, and Code/Skills that’s already replacing or improving how they handle at least three recurring tasks • Within the first quarter of the engagement, the client executive is a true power user — running multi-step workflows, custom Skills/Projects, and agent-assisted tasks without needing coaching scaffolding for the basics • A documented set of executive playbooks (research, writing, analysis, synthesis, workflow automation, agent-assisted tasks) that compound across every client engagement, not one-offs • A curated, current library of learning materials, videos, example workflows, and Claude-native patterns — including a clear point of view on which external courses, tutors, or expert resources are worth plugging in • Observable change in how client executive cohorts use AI: from reactive chat to repeatable, structured, outcome-oriented workflows • A foundation of training assets and patterns that scales beyond executive coaching into broader client teams in year two • A reputation among AIVC’s clients as the trusted go-to for “how do I do this better in Claude” — measured by inbound demand and engagement expansion What You’ll Do (Responsibilities) • In the first weeks: build the first client managing partner’s tailored upskilling plan — assess current usage, identify the highest-leverage workflows for their day-to-day, curate the right mix of materials / videos / course content, and recommend any tutor or expert-guided support to fold in • Provide 1:1 coaching for client executives — managing partners, founders, C-suite leaders — on Claude, Cowork, and code- and agent-based workflows • Design tailored training plans per executive that go beyond basic onboarding into advanced usage, with explicit progression from chat → workflows → agents • Curate the best external materials (videos, courses, blog posts, example projects) and rewrap them into client-ready, AIVC-flavored learning paths • Teach practical, high-leverage use cases live: research, writing, analysis, synthesis, workflow automation, and agent-assisted tasks • Help client executives move from general chat usage into repeatable workflows — Claude Projects, Skills, scheduled Cowork tasks, MCP integrations, custom agents • Serve as a real-time tutor and expert resource for client executives — over Slack, in meetings, on-site, and in async written feedback • Run office hours, workshops, and informal Q&A sessions inside client teams to keep adoption sticky between coaching sessions What We’re Looking For (Required) • Deep hands-on expertise with Claude across every surface (Claude.ai, Claude Projects, Claude Code, Claude Skills, Claude API) — and an active habit of pushing the edges of each • Strong working fluency with Claude Cowork specifically, including scheduled tasks, connected apps / MCPs, and the broader workflow surface • Strong capability with code-enabled AI workflows: you can write Python and/or TypeScript, build agents, configure MCP integrations, and ship a working internal automation end-to-end without needing an engineer • Demonstrated ability to teach non-technical but highly demanding users — you’ve made executives, founders, or senior operators meaningfully better at something complicated, not just trained engineers • Strong workflow design instinct — you can translate messy business questions into clean prompts, workflows, and systems • Polished, discreet, and effective in high-touch client executive settings — high EQ, low ego, comfortable representing AIVC inside senior client environments and around senior decision-makers • Strong bias toward practical results over theoretical AI knowledge — the metric is the client executive’s behavior change, not the elegance of the explanation • Excellent written and verbal communication; you can write a playbook a client executive will actually read and use • Comfort with significant travel to client sites and embedded, on-site engagement work • 5+ years of professional experience across some mix of: applied AI / ML, technical training and enablement, developer relations, solutions engineering, executive coaching, management consulting, or chief of staff / senior operator roles to executives Helpful If You Have (Preferred) • Prior experience coaching or supporting C-level executives, founders, or managing partners as a client-facing professional — executive coach, principal solutions engineer to executive customers, chief of staff to a CXO, or partner-level consultant • Background that combines technical depth with people skills — developer relations, solutions engineering, technical training, or learning & development at a frontier AI or developer-tools company • Direct experience building executive-facing training programs or curricula that demonstrably moved adoption inside other organizations • Hands-on familiarity with the Anthropic product surface specifically: Claude Projects, Claude Skills, Claude Code, MCP server development, Claude API • Track record of getting non-technical users to genuinely adopt a technical tool — i.e., users who chose to keep using it after the training ended • Background in management consulting, professional services, executive coaching, or learning & development — especially in environments where the customer was a senior external client • An active personal portfolio of AI work (workflows, automations, blog posts, talks, open-source contributions) you can point to • Comfort building light tooling (a Notion playbook system, a Claude Skills catalog, a small dashboard) without needing engineering support • Familiarity with AIVC’s model — operator business engagements, EBITDA-led measurement, and the broader compounding intelligence layer — or eagerness to come up the curve quickly

NobleProg is seeking an experienced AI Trainer to deliver a live, instructor-led remote training focused on helping technical professionals integrate Agentic AI and RAG systems into their existing workflows. This opportunity is designed for participants with strong technical backgrounds (Data Engineering and Workflow Automation) but limited formal AI experience, with the goal of applying AI to real-world systems rather than learning theory. Engagement Details Location: Remote Duration: 2 days Audience: Data Engineers and Workflow Developers Participants: 4+ Daily Rate $1,100 per day Course Scope This training focuses on practical, hands-on development of AI-powered systems using Retrieval-Augmented Generation (RAG) and agent-based architectures. The course will follow a Core & Split approach, starting with shared foundational concepts, moving into role-specific deep dives, and concluding with an integrated session demonstrating how AI systems are built and applied across workflows and data pipelines. NobleProg SOP - https://share.synthesia.io/a0788c6e-56d5-4da8-92c6-0d5c03ad6d52 Key Topics Include - Practical introduction to LLM applications and AI system architecture - Retrieval-Augmented Generation (RAG) design and implementation - Data preparation, embeddings, and vector database concepts - Agentic AI fundamentals (tools, decision-making, multi-step workflows) - Orchestration frameworks such as LangChain, LangGraph, or similar - Role-based applications: RAG pipelines for data engineers and AI-driven workflows for workflow developers - End-to-end system integration (RAG + agents + automation) Trainer Responsibilities - Deliver engaging, instructor-led remote training with strong hands-on focus - Translate AI concepts into practical applications for non-AI technical professionals - Structure delivery using a Core & Split model to address different roles - Provide real-world exercises aligned with data pipelines and workflow automation - Facilitate an integrated session demonstrating how different components work together - Prepare training materials (trainer retains ownership of content) Required Qualifications - Hands-on experience building LLM-based applications, including RAG systems and agent-based workflows - Strong proficiency in Python and experience with APIs, data pipelines, or automation systems - Experience with frameworks such as LangChain, LangGraph, or similar - Proven experience delivering technical training to engineering audiences - Ability to simplify AI concepts and connect them to real-world use cases Nice to Have - Background in data engineering, workflow automation, or solutions architecture - Familiarity with MCP or emerging agent orchestration frameworks - Experience designing modular or role-based training programs preferred - Experience building production-grade AI applications preferred https://docs.google.com/document/d/184VlJipyixkLNJ_HnP3aPt4YToedTUAlji_LxkuLhRU/edit?usp=sharing Please review and approve this tentative outline. We will be meeting with the client to determine whether they prefer a 1-day or 2-day delivery format. The agenda may require some adjustments based on the client's specific objectives, technical background, and areas of interest, which can be finalized during the trainer-client consultation call. Could you please review the proposed outline and let us know if you see any red flags, gaps, concerns, or topics that may require immediate attention? We would also appreciate any recommendations regarding scope, level of technical depth, hands-on exercises, or prerequisite knowledge that should be addressed before presenting this to the client. Thank you for your feedback. How to Apply Please include - A brief overview of your experience with Agentic AI and RAG systems - Your experience delivering technical or AI-focused training - Examples of AI systems or applications you have built - Your approach to teaching participants without formal AI background - Availability for remote delivery

Custom iPad Client Closeout, Feedback & Review Automation Platform Developer Project Overview We are a high-end residential design-build firm seeking a developer to create a custom iPad-based client closeout platform. The system will be used during final project walkthroughs to conduct a structured satisfaction survey, capture referrals and testimonials, generate personalized AI-powered review content, and guide homeowners through the Google Review submission process. Our goal is to create a seamless, professional experience that increases client engagement, captures valuable feedback, improves our online reputation, and strengthens long-term client relationships. This project will be used by our team in homeowners' residences during project closeout meetings and should be designed to be simple, intuitive, and completed in just a few minutes. Desired Workflow 1. Team member conducts an in-person closeout survey with the homeowner. 2. Responses are entered into the iPad application. 3. The system evaluates client satisfaction and identifies highly satisfied clients. 4. AI generates a personalized review draft based on the client's actual responses. 5. The client reviews and edits the review if desired. 6. The client enters or confirms their Google account information. 7. The system directs the client to our Google Review page and facilitates the review submission process. 8. Survey results, testimonials, referral opportunities, and review data are stored in a database and/or Google Sheets. Survey Questions The application should allow us to customize and modify survey questions over time. Initial questions may include: Overall Satisfaction * How satisfied are you with your overall experience? * Did the completed project meet or exceed your expectations? * Would you hire us again for future projects? Communication * Were we responsive to your questions and concerns? * Did you feel informed throughout the process? Design & Construction Experience * Were you satisfied with the design process? * Were you satisfied with the quality of workmanship? * Did our team effectively solve challenges that arose during the project? Referrals & Advocacy * Would you recommend us to friends or family? * Would you be willing to provide a referral? * Would you be willing to participate in a future case study or testimonial? Marketing Permissions * May we use photos of your project in our marketing materials? * May we use portions of your testimonial or review in our marketing materials? AI Review Generation Based on survey responses, the application should generate a natural, authentic review draft. Example: "Working with Marvista Design + Build was a wonderful experience. Their team was responsive, professional, and highly organized throughout the entire process. We especially appreciated their communication, attention to detail, and commitment to quality. The finished project exceeded our expectations, and we would gladly recommend them to anyone considering a remodeling project." The generated reviews should vary in language and structure so they feel authentic and personalized. Additional Features Testimonial Capture * Collect written testimonials * Optional voice-to-text testimonial entry * Store testimonials in a searchable database Referral Capture * Identify clients willing to refer others * Capture referral contact information * Track referral opportunities Net Promoter Score (NPS) * Include NPS scoring * Flag dissatisfied clients for internal follow-up * Prevent unhappy clients from being directed toward public review requests Reporting Dashboard * Review completion statistics * NPS tracking * Referral tracking * Testimonial tracking * Historical reporting Data Storage Preferred integrations include: * Google Sheets * Google Workspace * Airtable * Cloud database solutions We are open to recommendations. Technical Requirements We are open to the developer's recommendation regarding architecture and technology stack. Potential solutions include: * Native iPad application * React Native * Flutter * Progressive Web Application (PWA) * OpenAI API integration * Google Workspace integration * Airtable integration The solution should be easy to maintain and scalable for future enhancements. Future Vision This is intended to become Phase 1 of a broader client experience platform that may eventually include: * Automated review campaigns * Referral management * Client for Life program tracking * Testimonial library management * CRM integration * Marketing automation We are looking for a developer who can help us think strategically about the long-term roadmap, not simply build the initial application. Ideal Freelancer We are looking for someone who: * Has experience building custom business applications * Has experience with AI integrations * Has experience with survey platforms and workflow automation * Understands user experience and interface design * Can recommend the best technical approach * Can build scalable solutions that can evolve over time When Applying, Please Include 1. Examples of similar applications you have built. 2. Experience with AI-generated content and OpenAI integrations. 3. Experience with Google Workspace, Airtable, or CRM integrations. 4. Your recommended technical approach for this project. 5. Estimated timeline and budget range. 6. Any suggestions for improving the workflow described above. We are less concerned with a specific technology stack and more interested in finding the right development partner who can help us create an exceptional client experience.

I need a full-stack developer to build a simple AI-powered chat assistant. The app should allow users to type a question and receive a response from the ChatGPT API. The UI should be clean, responsive, and built with React and TypeScript. Main Requirements: - Build a simple React + TypeScript frontend - Add a chat input and response area - Connect the app to the ChatGPT/OpenAI API - Show loading state while the AI is responding - Handle basic API errors - Keep the code clean and easy to understand - Provide short setup instructions in a README file