About the Role Assembly Software is a B2B SaaS company serving law firm customers and is actively expanding its internal AI capabilities. We are seeking a highly skilled AI contractor to serve as our embedded AI program lead — someone who can own and advance the design, implementation, and governance of AI tooling across the entire organization. This is a hands-on, strategic role. You will work directly with IT leadership and cross-functional teams to assess our current AI landscape, close gaps, and build a mature, secure, and operationally excellent AI program. We are a heavy Anthropic/Claude shop. Strong familiarity with Claude, the Anthropic API, and the Model Context Protocol (MCP) ecosystem is a significant advantage for this role. Core Responsibilities • Audit existing AI tool usage and identify overlaps, gaps, and shadow IT • Design and implement a company-wide AI governance framework • Lead MCP server setup, integration, and lifecycle management • Configure and manage Claude Teams/Enterprise deployments • Build and maintain an internal AI Skill Library for staff use • Define AI security policies and data access controls • Evaluate and recommend new AI tools and vendors • Establish prompt engineering standards and best practices • Connect AI tooling to internal business systems (Salesforce, M365, Asana, and others) • Support AI integrations with sensitive data sources including our data warehouse and CRM • Produce documentation, SOPs, and executive-ready reporting • Train internal staff and stakeholders on AI capabilities and safe usage Required Qualifications • Hands-on AI implementation experience in enterprise environments • Deep familiarity with large language model platforms, particularly Anthropic Claude and OpenAI • Proven experience building and managing MCP (Model Context Protocol) servers and integrations • Strong understanding of AI security — data exposure risks, access scoping, governance controls, and audit logging • Experience integrating AI tooling with business systems such as Salesforce, Microsoft 365, or similar platforms • Ability to author clear governance documentation, security policies, and executive-facing deliverables • Comfortable operating independently with minimal oversight while maintaining strong stakeholder communication Preferred Qualifications • Hands-on experience with the Anthropic Claude API, including system prompt design, tool use, and agentic workflows • Background in B2B SaaS, legal technology, or other regulated industries • Familiarity with SOC 2 compliance requirements as they relate to AI tooling and data access • Prior experience standing up internal AI assistants or Copilot-style tooling connected to live business data • Knowledge of data warehousing and secure query patterns for LLM-to-database integrations • Familiarity with CI/CD workflows and lightweight DevOps for deploying AI services

About ZeremAI ZeremAI is a premier AI and Automation implementation consultancy that future-proofs businesses. We specialize in cutting-edge AI agents, intelligent systems automation, and real-time AI-assisted KPI dashboards across all business departments. Our "Align–Automate–Achieve" methodology bridges the gap between technology and measurable impact, helping teams reclaim up to five days of productivity weekly per employee, allowing organizations to focus on their core mission. Position Overview: We are looking for an AI Technical Account Manager who thrives at the intersection of systems architecture and client partnership. This role is for a high-presence communicator who takes pride and care about Customer Success and can translate complex AI and automation workflows into clear, actionable business wins and communicate them with the AI Development team. You are an AI Technical Account Manager at heart—someone who possesses the technical depth to design sophisticated systems but whose real superpower is leading the client relationship. You’ll be the face of our delivery team, ensuring our clients don't just get a tool, but a transformed business process they actually enjoy using. Key Performance Indicators (Success Metrics): -100% successful deployment rate of AI and automation solutions. -Ensure systems adoption success scores reach 95%+ -Increase customer productivity by 20% to 100%+ through AI automation. -Increase customer KPI achievement rate by 2x through intelligent dashboards. -Maintain 97% or higher customer satisfaction rating for solution delivery. Core Client Responsibilities: Strategic Client Leadership: - Relationship Management: Act as the primary technical point of contact, managing expectations and leading clients through the "Align–Automate–Achieve" journey with confidence. - High-Impact Communication: Lead discovery calls and project updates with clarity and brevity. You are the concise expert—getting to the point quickly and making complex concepts clear and simple to non-technical customers. - Client Success Orientation: Prioritize the "human" side of the implementation, ensuring the solution solves the client’s actual pain points rather than just being technically correct. Solution Architecture & Discovery: - Workflow Mapping: Conduct process audits to identify gaps and translate messy business problems into clean system requirements. - High-Level Design: Architect automation ecosystems using Make, Zapier, Airtable, HubSpot, and other systems, ensuring all pieces of the tech stack talk to each other seamlessly. - AI Integration: Leverage LLMs (OpenAI, Claude, etc.) to enhance productivity and build smarter business logic for clients. Delivery & Adoption: - Implementation Oversight: Work with the internal dev team to ensure the blueprints you designed are built to spec and delivered on time. - The Final 10%: Lead the hands-on training and documentation phase, ensuring the client’s team feels empowered and capable, not overwhelmed. - Iterative Optimization: Monitor performance post-launch and proactively suggest enhancements to deepen the client relationship. Key ZeremAI Operations Responsibilities: - Collaborate with the Chief AI Officer and Strategy Officer to evolve ZeremAI’s systems playbook. - Lead the evaluation and adoption of new AI technologies and platforms. - Ensure solution designs align with the Align–Automate–Achieve methodology. - Create internal system frameworks, templates, and automation best practices. - Mentor and collaborate with AI Systems Developers to maintain high-quality standards. - Analyze reporting on architecture performance, ROI metrics, and adoption rates. The Ideal Profile: Technical Fluency (The "How It Works" Knowledge): - Systems Thinker: You understand the Big Picture of how APIs, CRMs, and databases interact. You don’t need to be the world’s fastest coder, but you must be a world-class architect. - Automation Stack: Deep familiarity with CRM, Project Management, Integration, and AI tools. - AI Expert: A solid grasp of how to practically apply AI/LLMs to business workflows. The Superpowers (Client & Communication): - Professional Presence: You carry yourself with a demeanor that builds immediate trust. You are concise, articulate, and mindful of the client’s time. - Concise Communicator: You avoid the Solution Architect Trap of over-explaining. You know how to give a "Yes/No" or a "Bottom Line Up Front" (BLUF). - Leadership: You can guide, educate, and—when necessary—firmly pivot a client toward a better strategic path. Qualifications: Required Skills & Experience - 5+ years of experience in systems consulting, operations, business automation, or a similar role. - 2+ years of AI expertise in a business context - Strong hands-on experience with automation tools (JSON, Zapier, Make, Airtable, etc.) and system integrations. - Working knowledge of project management and CRM platforms (e.g., Monday.com, HubSpot, Salesforce). - Familiarity with API usage, data flows, and basic scripting or logic-based automation. - Excellent problem-solving and process-mapping skills. - Clear written and verbal communication, especially with non-technical stakeholders. - Strong client-facing presence with the ability to guide, educate, and influence clients. Preferred Qualifications: - Experience in a fast-paced startup or agency environment. - Exposure to AI tools and understanding of their application in business settings. - Technical certifications in automation platforms (Zapier Expert, Make Partner, etc.). - Understanding of business functions like marketing, sales, operations, and finance. Soft Skills: - Demonstrate creativity in problem-solving by identifying innovative solutions to client challenges and operational obstacles. - Systems thinker with a knack for breaking down complex problems. - Highly organized, self-motivated, and able to manage multiple client projects simultaneously. - Collaborative team player who thrives in a remote-first work environment. - Passionate about technology, continuous improvement, and client success.

We are looking for a strong software engineer who can build practical automation systems using AI, APIs, and modern development tools. This role is for someone who can take messy business workflows, understand the goal, and build working systems that save time, reduce manual work, and improve execution. You should be comfortable building automations, integrating tools, working with APIs, writing clean code, and using AI tools like OpenAI, Claude, or similar models to create useful business applications. What You’ll Work On You will help build and improve systems such as: AI-powered research and data extraction workflows CRM and sales process automations Email, spreadsheet, and database automations Internal tools and dashboards API integrations between business software Web scraping and data enrichment workflows when appropriate AI agents or assistants that help with repetitive business tasks Automation around deal screening, reporting, lead research, and document creation Ideal Candidate We are looking for someone who is practical, fast, and can figure things out without needing step-by-step instructions. You should have experience with: Python and/or JavaScript APIs and webhooks OpenAI, Claude, or other LLM APIs Automation tools like Zapier, Make, n8n, Airtable, Google Sheets, HubSpot, Salesforce, or similar Databases such as PostgreSQL, Supabase, Firebase, or similar Basic front-end or internal tool development Web scraping, data cleaning, and structured data workflows GitHub and clean documentation What Matters Most We do not need someone who only talks about AI. We need someone who can actually build. The right person should be able to: Understand a business process quickly Recommend the simplest technical solution Build fast prototypes Turn prototypes into reliable workflows Communicate clearly Document what was built Improve systems over time Nice to Have Experience with any of the following is a plus: Private equity, M&A, finance, or investment workflows Deal sourcing or lead generation systems CRM automation Data enrichment tools AI research agents Browser automation Cloudflare, AWS, Google Cloud, or similar infrastructure Engagement This will start as a part-time project-based role, with the potential to become ongoing if the work is strong. Estimated workload: 5 to 15 hours per week to start. To Apply Please include: Examples of automations or AI tools you have built The tech stack you usually work with A brief explanation of how you would approach automating a messy manual workflow Your hourly rate Your availability Please do not send a generic application. If your response looks copied and pasted, it will be ignored.

We are looking for an experienced full-stack developer with strong AI-assisted development skills to help us transform our existing payment administration web platform into a modern application. We operate a payment management/admin system and want to accelerate development using AI tools such as Cursor, Claude, ChatGPT, GitHub Copilot, or similar technologies. The goal is to rapidly build, improve, and scale our payment administration platform while maintaining high code quality and security standards.

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.

I need a commerical made for my Mobile Barbershop. I have pictures and videos to share But I would like the video to contain me and my van so it seems like an authentic add

### Job Description: AI Chatbot Developer We are excited to announce an opening for an experienced and innovative developer to join our dynamic team in the pursuit of creating an advanced AI Chatbot. This chatbot will be designed to perform essential business functions, including but not limited to lead generation, quoting, and providing exceptional customer support. Our ideal candidate will possess a robust background in AI technologies, particularly in the realm of chatbot development, and will be equipped with outstanding problem-solving skills that enable them to tackle complex challenges with creativity and efficiency. As a key member of our development team, you will collaborate closely with various departments to gain a comprehensive understanding of our specific operational needs and requirements. Your ability to translate these needs into a functional and user-friendly chatbot solution will be critical to enhancing our overall operational efficiency. We are looking for someone who is not just technically proficient but also possesses a keen sense of business acumen to ensure that the chatbot aligns with our strategic goals. In this role, you will be responsible for various aspects of the chatbot development lifecycle, including but not limited to: - Designing and developing the conversation flow and user interface of the chatbot, ensuring it is intuitive and engaging for users. - Implementing natural language processing (NLP) capabilities to enable the chatbot to understand and respond to user inquiries accurately. - Integrating the chatbot with existing systems and databases to facilitate seamless access to information necessary for lead generation, quoting, and customer support functions. - Conducting rigorous testing and quality assurance to ensure the chatbot performs reliably and meets user expectations. - Analyzing user interactions and feedback to continuously improve the chatbot's performance and expand its capabilities over time. - Staying current with the latest advancements in AI technologies and chatbot development to incorporate best practices and innovative solutions. You will also play a crucial role in training team members on how to utilize the chatbot effectively and will be expected to provide ongoing support and maintenance to ensure the chatbot remains up-to-date and functional. If you have a passion for artificial intelligence, a deep understanding of customer engagement strategies, and a desire to make a significant impact within our organization, we would love to hear from you! Join us in revolutionizing the way we interact with our customers and streamline our business processes through cutting-edge technology. This is a fantastic opportunity for someone looking to advance their career in a fast-paced, forward-thinking environment. Apply today and be part of our exciting journey towards enhancing our customer experience through AI!

I am a partner at a recruiting firm seeking a conversational AI tool to enhance our communication with candidates and clients. Our business is highly conversational, and we primarily use LinkedIn and Loxo. We need a tool that can efficiently manage and personalize our interactions, potentially integrating with our existing platforms.

About Us Paragon International, Inc. is a U.S.-based manufacturer of commercial concession equipment and food service products. We receive purchase orders from customers such as Amazon, Home Depot, distributors, school systems, and other commercial customers. Orders arrive by email in many different formats, including PDFs, Word documents, Excel spreadsheets, scanned documents, and occasionally photographed purchase orders. We are looking for an experienced AI Automation Engineer to design and build a production-ready system that automates our entire order intake process. This is not a simple chatbot project. We need someone who has successfully built business automation systems that combine AI, OCR, document processing, APIs, and workflow automation. Project Overview The system will monitor one or more Gmail inboxes continuously and automatically process incoming emails and attachments. The workflow should: * Monitor Gmail 24/7 for new incoming emails. * Download all attachments automatically. * Read: * PDF files * Microsoft Word documents * Excel spreadsheets * Scanned PDFs * Image files (JPG, PNG, TIFF, etc.) * Photographs of purchase orders * Use OCR when required. * Use AI to determine whether the email is: * Purchase Order * Quote Request * Cancellation * Return/RMA * Customer Inquiry * Other * Identify the customer automatically. * Extract all order information into a standardized data structure. * Detect duplicate purchase orders. * Automatically print valid purchase orders to our network printer. * Save documents into organized folders. * Rename files using a consistent naming convention. * Move processed emails into Gmail folders/labels. * Generate logs for auditing and troubleshooting. ## Future Phases The initial project focuses on reliable document processing and printing. Additional phases may include: * Sage 100 ERP integration * Automatic sales order creation * Inventory verification * Customer acknowledgment emails * Shipping workflow automation * Dashboard and reporting * AI exception handling * Multi-location printing We are looking for a long-term development partner who can continue improving the system over time. ## Required Skills Please apply only if you have strong experience with most of the following: * OpenAI API / ChatGPT API * Gmail API * OCR technologies (Tesseract, Azure Document Intelligence, Google Vision, AWS Textract, or similar) * Intelligent Document Processing (IDP) * PDF parsing * Workflow automation * Python * REST APIs * Windows automation * Network printing * Error handling and logging * AI document classification Experience with the following is a significant advantage: * n8n * Microsoft Power Automate * Make.com * ERP integrations * Sage 100 * Purchase Order processing * Manufacturing or distribution businesses ## Deliverables The completed solution should: * Run continuously with minimal supervision. * Be reliable enough for production use. * Handle errors gracefully. * Be well documented. * Be easy for our staff to maintain. * Be scalable as our order volume grows. ## To Apply Please include: 1. A description of similar automation projects you have completed. 2. Which automation platform you recommend (Python, n8n, Power Automate, Make, or another solution) and why. 3. Examples of AI document processing or OCR projects you've built. 4. Your experience integrating with ERP systems. 5. Your estimated timeline. 6. Your hourly rate or fixed-price proposal. Please begin your proposal with the phrase: **"I have built AI document automation systems."** This helps us identify applicants who have carefully read the project description. We are looking for a long-term partner, not just someone to complete a single project. If this project is successful, additional work will include ERP integration, warehouse automation, customer service automation, purchasing automation, and AI-driven business process improvements.

We need a senior architect to design and build a multi-model routing control plane, then lead a small senior team through the build. The control plane sits in front of a family of AI systems and decides, per request (text, image, video), the optimal path across cost, quality, latency, business value, and sovereignty (data residency, rights, and cultural fit): cache and reuse, a small or on-device model, an open-weight, fine-tuned, or sovereign model, or a higher-cost frontier fallback. It routes across compute too: CPU, GPU, inference accelerators, on-device, and edge. Core KPIs: the share of eligible workload kept off frontier accelerators and the resulting cost reduction on a representative workload, plus sovereignty compliance, with no quality regression. This is not a chatbot and not a wrapper over hosted APIs. You own the architecture, define the routing logic, and lead execution. You think in systems, not individual model calls. Context The router is one component of a larger AI platform. It must be model-agnostic: open-weight, fine-tuned, and proprietary models swap in and out behind a stable interface without rearchitecting. A separate team owns the models you route to. The engagement is a 60 to 90 day POC with a working router demo (text-first, with a defined path to image and video), followed by technical leadership through the build. What you'll own Control plane: intake and normalization, classification, routing taxonomy, model-selection logic, fallback hierarchy, cache and reuse rules, telemetry, and the eval feedback loop. Routing that is learned and calibrated, not just static rules: predict per-query difficulty and expected quality, and escalate on confidence thresholds. Comfort with cascades and speculative decoding is expected. Routing across cost, quality, latency, and policy. In constrained environments some requests must stay local regardless of cost. Model-agnostic interface: clean, stable contracts so models and execution paths swap without rework, and the separate model team can work independently of the routing layer. Cost optimization across compute: exact and semantic cache, prefix/KV cache reuse, output reuse, batching, small-model routing, CPU offload, and on-device/edge execution, with a clear fallback hierarchy. The goal is to move most eligible workload off frontier accelerators without degrading output. Generative caching and reuse: caching text is easy; image and video are not, since the same prompt should produce variation rather than an identical result. We need credible reuse at the asset or component level, not just for text. Eval loop: scores output quality by domain and flags weakness so the training team can target fixes instead of retraining broadly. Track quality vs intent, failure modes, cost per route, latency per route, cache hit rate, fallback rate, and regeneration rate. Execution and leadership: architecture blueprint, POC scope, milestones, infra assumptions, and risks leadership can review, plus hands-on architecture review and task breakdown. You'll lead a small senior team, and one of your first deliverables is recommending its exact composition (see screening questions). Ideal background Led or architected production AI infrastructure across several of: multi-model orchestration and LLM routing, multimodal, model serving, inference cost and GPU reduction, CPU and on-device inference, open-source and fine-tuned deployment, cascades and speculative decoding, semantic and prefix caching, eval pipelines, and AI observability. Deployed in at least one constrained environment: on-prem, self-hosted, air-gapped, or data-residency-restricted. You know what breaks when you can't lean on a single cloud. Can lead: set architecture, break down work, review the team's output, and keep the build on track. Tools matter less than the ability to architect the system correctly and lead execution. Not a fit: basic chatbot workflows, hosted APIs only, or prompt engineering alone. Deliverables Control plane blueprint, routing taxonomy, POC plan with milestones and success criteria, and an eval/feedback framework, with a working router demo as the 60 to 90 day target, then technical leadership of a small team through the build. Screening questions The most relevant AI routing, model-serving, or inference infrastructure system you personally designed or built: what was routed, which models or execution paths, and what role did you own? How would you design a router that chooses between cache/reuse, a smaller or local model, an open-weight or fine-tuned model, or a frontier fallback, across CPU and GPU? Where do learned routing, cascades, or speculative decoding fit? For generative image or video requests, how would you approach caching or reuse when the same prompt should still allow variation? Be specific. What metrics and eval loop would you use to prove the router cuts cost without degrading quality, and to help a separate training team find weaknesses? Beyond yourself, what team would you staff to hit these deliverables in 8 weeks? Give the roles, seniority, and headcount, how you'd split the work, and flag any deliverable that 8 weeks and a team of roughly 4 engineers can't realistically cover. To apply Answer the five questions, summarize your most relevant routing or inference-infrastructure work (repos, writeups, talks, or architecture you can describe), and give your high-level approach to a control plane that routes across cost, quality, and sovereignty while preserving quality. Note your availability, your rate, whether you've led a small engineering team before, and the team you'd staff to hit the deliverables in 8 weeks.