# Founding AI Operations Architect | Build the Future of Home Services ## About EPIC EPIC Septic & Service is one of the fastest-growing septic and wastewater companies in America. We are a veteran-owned organization with operations expanding across multiple states and an ambitious vision to become the first nationally recognized brand in the septic and wastewater industry. But we're not just building a septic company. We're building the operating system behind it. Our mission is to create the first AI-powered Virtual Back Office (VBO) for the septic and wastewater industry—combining customer service, dispatching, sales, inspections, maintenance agreements, reporting, and franchise support into a single scalable platform. We believe the future of home services is not simply hiring more people. We believe the future is AI-powered operations supported by exceptional field teams. ## The Opportunity We are seeking a Founding AI Operations Architect to help design, build, and implement the technology infrastructure that will power EPIC's next phase of growth. This is not a traditional software development role. This is a systems architecture and operational design role focused on leveraging AI, automation, and modern technology to transform how a service business operates. You will work directly with the founder and executive team to map processes, identify opportunities for automation, and build the foundation for a platform that can scale across company-owned locations, franchisees, and strategic partners nationwide. We are looking for a builder, an operator, and a visionary who enjoys solving complex operational challenges with technology. ## What You'll Build ### Customer Experience Systems * AI-powered call answering * Lead qualification and routing * Appointment scheduling * Customer communication workflows * Automated follow-up sequences ### Revenue Operations * AI sales agents * Estimate and proposal generation * Maintenance agreement enrollment * Payment collection workflows * Customer retention programs ### Field Operations * Dispatch automation * Technician scheduling * Inspection workflows * Service reminders * Work order management ### AI Agent Ecosystem * Customer Service Agent * Dispatcher Agent * Sales Agent * Collections Agent * Inspection Report Agent * Franchise Support Agent * Internal Operations Assistant ### Reporting & Intelligence * Executive dashboards * Operational scorecards * Franchise performance reporting * KPI monitoring * Business intelligence systems ## Current Technology Stack We are currently evaluating and implementing technologies including: * Jobber * Claude * UJET * Make * n8n * Zapier * Airtable * Retool * Custom APIs and integrations We are open to recommendations from the right candidate. ## First 90-Day Objectives ### Phase 1 – Discovery & Architecture * Audit current EPIC workflows * Map customer journeys from lead to completion * Identify automation opportunities * Design overall system architecture * Create implementation roadmap ### Phase 2 – MVP Development * AI phone answering workflows * Lead qualification automation * Scheduling automation * Estimate generation workflows * Customer communication systems ### Phase 3 – Virtual Back Office Launch * Dispatch automation * Maintenance agreement workflows * KPI dashboard implementation * Reporting framework * Initial franchise-ready operating model ## Ideal Experience You have successfully built or implemented: * AI agents and automation systems * Contact center automation * CRM integrations * Workflow automation platforms * Field service management systems * Operational software for service businesses * Multi-location or franchise support systems Bonus experience includes: * Jobber * ServiceTitan * Home service businesses * Plumbing, HVAC, electrical, septic, or wastewater industries * Franchise operations * AI-powered customer support systems ## What We're Not Looking For Please do not apply if you are: * A website designer * Looking for simple development tasks * An agency that outsources work * Someone without hands-on AI automation experience * Someone who has never built operational systems that drive real business outcomes We are looking for someone who can think strategically, architect systems, and execute. ## Why This Opportunity Is Different Most companies use AI to make small improvements. We are using AI to reimagine how an entire industry operates. Our goal is to create the first fully AI-enabled septic and wastewater platform in America and ultimately build the infrastructure that powers operators nationwide. This is an opportunity to help build something from the ground up, have a direct impact on the direction of the platform, and work alongside a team that is committed to innovation, execution, and long-term growth. ## To Apply Please include: 1. Examples of AI systems you have designed or built. 2. Relevant automation or operational projects. 3. CRM or field-service integrations you have implemented. 4. Your preferred technology stack and why. 5. How you would approach building an AI-powered Virtual Back Office for a service business. 6. What excites you most about this opportunity. We are looking for a long-term partner who wants to help build something meaningful, scalable, and industry-defining.

We are looking for a skilled full-stack developer to implement precise feature updates and frontend optimizations on our AI-powered, agentic test automation platform. The ideal candidate must have proven expertise in React, Node.js, and TypeScript, alongside a sharp eye for clean UI/UX implementation and seamless API integrations. In this role, you will be responsible for modifying existing frontend components, refining backend API endpoints to support layout adjustments, and ensuring a bug-free, highly responsive user experience. This is a scoped, short-term contract requiring a developer who can jump straight into a production codebase, follow system architecture standards, and deliver clean, well-tested code efficiently.

We’re looking for an experienced engineer or trainer to help deliver hands-on AI coding training for engineering teams. The focus is on moving engineers beyond basic Copilot/autocomplete usage into agentic workflows with tools like Claude Code, Codex, GitHub Copilot, and related tooling. Scope: Run practical workshops for engineers Teach Claude Code, Codex, and Copilot workflows Cover task scoping, prompting, reviewing diffs, and code validation Help create assets like CLAUDE.md, agents.md, slash commands, or workflow templates Advise on best practices, cost awareness, security, and team adoption Ideal candidate: Strong software engineering background Hands-on experience with Claude Code, Codex, or similar tools Experience training engineering teams Clear communicator with practical examples Please apply with relevant examples of AI coding workflows, trainings, or engineering teams you’ve supported.

Overview I have a Next.js website with a newsletter signup form that currently submits directly from the browser to HubSpot's Forms v3 endpoint. I want to add a lightweight LLM-based spam filter that inspects each submission *before* it reaches HubSpot, and silently rejects (or flags) anything that looks like spam/bot/junk input. Current setup - Framework: Next.js (App Router, TypeScript, React client component) - The form component (`NewsletterForm.tsx`) POSTs directly to `https://api.hsforms.com/submissions/v3/integration/submit/[portalId]/[formGuid]` - Fields collected: `firstname`, `lastname` (optional), `jobtitle`, `email` - Portal ID and Form GUID are public form identifiers (no secrets today) What I want you to build 1. Create a server-side API route in the Next.js app (e.g. `app/api/subscribe/route.ts`) that: - Receives the form fields from the client - Runs an LLM spam/quality check (e.g. OpenAI or similar) to classify the submission as legit vs. spam — checking for gibberish names, fake/disposable emails, nonsense job titles, injection attempts, etc. - If legit → forwards the submission to HubSpot (server-side) - If spam → rejects gracefully with a generic message (no HubSpot write) 2. Update the existing `NewsletterForm.tsx` to POST to the new internal API route instead of calling HubSpot directly. 3. Keep the LLM API key server-side only (use an environment variable — never expose it to the client). 4. Preserve the existing UX: loading / success / error states should still work. Deliverables - Working API route with the LLM spam check + HubSpot forwarding - Updated form component - Brief note on which env vars to set (`OPENAI_API_KEY`, etc.) and how to configure them - Clean, typed TypeScript that matches the existing code style Nice to have (optional) - Basic rate limiting / honeypot field as a cheap first line of defense before the LLM call - Configurable spam threshold or a logged "reason" when something is rejected Requirements to apply - Strong Next.js App Router + TypeScript experience - Experience calling an LLM API (OpenAI or equivalent) from a server route - Familiarity with HubSpot Forms API is a plus To apply, please briefly answer: 1. Which LLM/provider would you use and roughly what would it cost per submission? 2. How would you handle the case where the LLM API is slow or down — do you fail open (let it through) or fail closed (block it)? 3. Have you integrated with HubSpot Forms before? (yes/no is fine)

Forum Intelligence: Project Brief & Initial Rollout 1. Executive Summary & Objective Forum Intelligence is a beginning as a localized data retrieval, processing, and archiving system designed to scrape public municipal records and state legislative data for public oversight. The immediate objective is to build a functional, highly resilient prototype focused on the Tri-Cities region (Burbank, Glendale, and Pasadena, California). The system will autonomously ingest messy, unstructured municipal data (City Council meeting minutes, agendas, public notices, and legislative PDF text, recorded mp4), clean it, and make it fully searchable and queryable via a localized AI agentic framework. 2. Phase 1 Scope: The Tri-Cities Rollout Th engineer will be responsible for building two primary pillars: A. Resilient Scraper Bots • Target Ingestion: Monitor and pull data from Burbank, Glendale, and Pasadena municipal portals and California legislative feeds. • Data Types: Brittle HTML sites, heavily nested tables, public notices, legislative drafts, and massive unstructured PDF archives. • Requirements: The scraping architecture must be exceptionally robust, utilizing intelligent error handling, retry semantics, and pagination tracking to handle frequent municipal website layout changes without breaking the pipeline. B. Ingestion & Vector Pipeline • Parsing: Extracting clean text from poorly formatted documents and scanned PDFs. • Local RAG (Retrieval-Augmented Generation): Chunking and embedding the data locally into a vector database (e.g., pgvector, Chroma, or Milvus) to enable semantically accurate entity linking and contextual search. 3. Targeted Hardware Stack To ensure maximum data security, strict public oversight integrity, and predictable operational costs, Forum Intelligence is skipping commercial cloud APIs in favor of an on-premise, localized NVIDIA enterprise deployment. The production roadmap aligns precisely with the new computing patterns detailed in NVIDIA’s latest hardware roadmap: • Inference & Token Generation: Running local open-weight frontier models (e.g., Neotron 3 Ultra or Claude/Llama equivalents) optimized for reasoning and long-context tool use. • Compute & Orchestration: The backend infrastructure is architected around NVIDIA’s dedicated agentic architecture, utilizing high-instructions-per-clock (IPC) Vera CPUs paired with Vera Rubin GPUs. • Memory & Storage Processing: Utilizing NVIDIA’s unified memory fabric and data processing units (DPUs) for ultra-low latency context management, KV caching, and fast vector database retrieval. 4. Immediate Milestones for the Engineer 1. Architecture Design: Map out the database schema and local inference ingestion loop. 2. Tri-Cities Scraper Deployment: Write and deploy the initial automated bots for Burbank, Glendale, and Pasadena. 3. Local MVP Pipeline: Demonstrate a local RAG pipeline where a user can query the Tri-Cities scraped records and receive grounded answers with exact source attributions. The above was AI generated from months long conversations with Gemini. The goal is to prove the concept then roll out to LA County, state of CA, and then the country.

I need someone to help me set up automation agents in Claude Cowork. My photo agency requires CoWork to watch a directory for new files and trigger a workflow. The ideal candidate will have experience in automation and workflow management, ensuring seamless integration with our directory to automate file processing.

We’re hiring an extraordinary developer to own and grow our Base44 apps and sales products. around the future of AI discovery 1. Future of AI Discovery Core Demo – https://pull-discovery-core.base44.app/ You’ll evolve https://pull-discovery-core.base44.app/ into a beautiful, fluid, high‑performance, full-functional future of AI discovery demo following our advanced and sophisticated technical blueprint Integrate and orchestrate AI models incorporating LLM's, Search and World Models into a seamless experience with no visible seams between UX and intelligence. Own front‑end performance, responsiveness, and micro‑interactions—animations, transitions, and state changes should feel intentional and “alive,” not bolted on. Implement robust logging and analytics to understand how users explore, where they get stuck, and how the discovery engine can adapt dynamically. 2. Book Sales Engine – Six‑Channel Publishing System The second current Base44 project is a system that operationalizes our comprehensive sales plan across six channels. SEE THE COMPREHENSIVE BOOKSALES PLAN ATTACHMENT UNDERNEATH THIS POSTING You will: Translate a detailed multi‑channel publishing strategy (KDP optimization, physical bookstores via IngramSpark, other digital platforms, libraries, bulk institutional sales, and authority‑engine content marketing) into concrete workflows, tools, and dashboards. Build internal interfaces and automations to: Track metadata, pricing, and promotions across Amazon KDP and other platforms. Monitor campaigns across TikTok, Meta, LinkedIn, YouTube, newsletters, and partnerships. Surface KPIs like BSR, review velocity, ad spend, email growth, library adoptions, and bulk orders in a single, coherent view. Design light internal UIs that make it easy for non‑technical team members to update copy, add titles, trigger campaigns, and view performance without breaking anything. Implement robust, testable integrations between Base44, external APIs, and data sources to keep everything in sync as we scale from 8 to 22+ titles and beyond. Who You Are We’re not looking for a generic “full‑stack dev.” We’re looking for an unusual combination of visionary and doer: Creative technologist mindset – You think in systems and interfaces at the same time. You care deeply about how a product feels as well as how it works. Obsessed with execution – You’re disciplined, structured, and relentless about shipping. You break ambiguity into sprints, reduce complexity into tickets, and never let projects stall. Proactive owner – You don’t wait for instructions. You propose better ways to do things, flag risks early, and bring options—not problems—to every conversation. Strong product sense – You can balance ideal UX with realistic constraints and understand when to ship v1 vs. when to invest in polish. Comfortable with complexity – Multi‑channel distribution, layered data flows, and evolving requirements don’t scare you; they energize you. Ideal Skills & Experience You don’t need all of these, but you should recognize yourself in most: 5+ years building production web applications, ideally with a strong front‑end/UI focus. Deep experience with modern web stacks (React/Vue/Svelte or similar) and TypeScript, plus comfort with Node or comparable back‑end runtimes. Strong visual/UI instincts: experience collaborating with designers or owning design yourself for data‑rich interfaces and dashboards. Experience integrating AI/LLM APIs and retrieval systems into real products (RAG flows, multi‑step tool use, chat‑like interfaces, recommendation engines). Experience with analytics and experimentation: event tracking, funnel analysis, A/B testing. Familiarity with publishing, ecommerce, or multi‑channel marketing systems is a plus (KDP, IngramSpark, email platforms, ad platforms, analytics). Prior work in environments like Base44 or other low‑code/agentic platforms is a strong plus, but not required if you learn fast.

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

I need an expert on Co pilot studio with a specific focus on agent optimization workflows. I have a handful of agents I need to work in parallel with one another and funnel up through a hierarchy to the master agents above. Looking to consult an expert to make this flow seamless, fast, and accurate for a project. Thanks!