Overview We run an AI voice assistant for self-storage operators. We have an internal, AI-assisted workflow for triaging call feedback — investigating what happened on a call, diagnosing the root cause in our codebase, and drafting fixes. We’re looking for someone technical to run that AI-assisted workflow day to day and help us make it better. You’ll be driving AI coding agents, reading real code to understand behavior, and improving the process and tooling itself. What you’ll do Use our AI agent tooling to work through a queue of customer feedback on AI voice calls. Read our TypeScript/Node codebase (voice-agent prompt assembly, workflow/“SOP” engine, tool implementations) to diagnose why the agent behaved a certain way — not just guess. Draft fixes: workflow-instruction edits, knowledge-base entries, or code changes via pull request with a clear verification plan. Improve the triage process itself — refine the AI agent prompts/skills, conventions, and the internal MCP tooling that powers it. Write clear, customer-facing summaries of what changed for our team to review and approve. You’re a great fit if you Read and reason about code confidently — ideally TypeScript/Node; React a plus. Have hands-on experience driving AI coding agents (Claude Code, Cursor, or similar) and understand how LLM prompts/tools/agents fit together. Think in cause-and-effect: “the agent did X because line Y / instruction Z.” Write precisely and concisely for both technical and non-technical audiences. Are process-minded — you spot the repetitive thing and turn it into a better workflow. Bonus: prompt engineering, LLM tool/agent development, or voice/conversational AI experience. How we work We’ll start with a paid trial on a small batch, then scale steady ongoing volume. To apply: Tell us about a time you used an AI coding agent to diagnose or fix something non-trivial in a codebase you didn’t write — what you did, and how you verified it worked. A link to relevant work is a plus.

Title: Backend Developer — AI Data Pipeline, Vector DB & Real-Time Push API Post: We are building an automated backend system that continuously crawls public web sources, processes and indexes content using AI, and delivers updates via webhooks. Looking for someone who has built this type of system before and can move fast. NDA required before project details are shared. What you’ll build: • Web crawler network —. • AI processing pipeline — cleans, deduplicates, chunks, and embeds ingested content into a vector database using an LLM embedding model. Quality scoring and incremental updates required. • Push API — monitors for significant content changes and delivers updates via webhook endpoints automatically. Includes configurable push schedules per subscriber, REST query endpoint, API key authentication, and token usage tracking per key. Tech stack (flexible — use what you know best): • Python (FastAPI) or Node.js • Any vector DB — Pinecone, ChromaDB, Supabase • Any LLM API — Anthropic or OpenAI • Any scheduler — n8n, APScheduler, cron • Redis for queue management • Railway, Render, or AWS for deployment Requirements: • NDA signed before kickoff — non-negotiable • Must have built RAG pipelines or vector DB systems in production — not tutorials • Must have experience with web crawlers and scheduled job pipelines • Must have experience with webhook delivery systems • GitHub or portfolio showing relevant deployed work required • 95%+ Job Success Score preferred • Individual contractors only — no agencies To apply include: • Example of a similar system you’ve built — web crawler, RAG pipeline, or push notification API • Your preferred stack for this type of build • Brief technical approach in 3–5 sentences • Hourly rate and availability to start Budget: $50–$80/hr Timeline: 3 weeks — focused sprint with daily check-ins

We are seeking an AI Automation Implementation Expert to enhance our business processes. The ideal candidate will have experience in implementing AI solutions to improve efficiency and productivity. Responsibilities include analyzing current systems, identifying areas for automation, and implementing AI-driven solutions. The candidate should be able to work independently and provide insights on AI best practices.

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)

We are a small residential real estate investment company seeking an AI Solutions Architect to enhance our acquisition platform. The role involves designing and implementing AI solutions to improve data analysis and decision-making processes. The ideal candidate will have experience in AI architecture and a strong understanding of real estate data analysis.

The Client seeks an experienced AI development team to design and build a secure web-based document intelligence platform capable of analyzing multiple related documents, extracting key information, identifying inconsistencies, and generating issue reports. The platform will support complex document sets where information must remain consistent across multiple files and versions. The initial scope focuses on document ingestion, data extraction, cross-document analysis, issue identification, and reporting. Business Objective Develop a scalable SaaS application that enables users to: • Upload and organize multiple related documents • Extract key terms, dates, parties, financial values, and references • Compare information across documents • Identify inconsistencies and missing information • Generate issue reports and review summaries • Maintain document version history • Provide an intuitive dashboard for issue management Phase 1 – Document Ingestion and Processing Requirements Develop a secure document upload module supporting: • PDF • Microsoft Word (.docx) • Microsoft Excel (.xlsx) • Text files System shall: • Extract text from uploaded files • Preserve document structure • Capture headings and section hierarchy • Process tables and schedules • Index document content for search and retrieval Phase 2 – Data Extraction Engine The platform shall automatically identify and extract: • Defined terms • Parties and entities • Dates • Numerical values • References to exhibits and schedules • Section references • Key metadata Extracted information shall be stored in a searchable database. Phase 3 – Cross-Document Consistency Review The platform shall compare extracted information across multiple documents and identify: • Inconsistent terminology • Conflicting dates • Conflicting numerical values • Missing references • Undefined terms • Duplicate provisions • Broken cross-references Examples include: • Same entity referenced using multiple names • Different numerical values for the same item • References to sections that do not exist • Missing exhibits or attachments Phase 4 – AI Review and Issue Identification The platform shall integrate a Large Language Model (LLM) to perform contextual analysis. The AI engine shall: • Summarize document contents • Identify potential drafting inconsistencies • Highlight missing information • Generate issue descriptions • Assign issue severity levels • Provide suggested corrective actions Phase 5 – Dashboard and Reporting Develop a web-based dashboard including: Transaction Workspace • Document list • Upload history • Processing status • Review status Issue Tracker • Issue category • Issue severity • Source document • Description • Resolution status Search Functionality Search by: • Term • Date • Party • Numerical value • Document name Reporting Generate downloadable reports in PDF and Excel format. Technical Requirements Frontend • React or Next.js Backend • Python • FastAPI preferred Database • PostgreSQL Vector Database • Pinecone, Weaviate, or Chroma AI Integration • OpenAI API • Anthropic API • Retrieval-Augmented Generation (RAG) architecture preferred Security Requirements • User authentication • Role-based permissions • Encrypted document storage • Audit logging • Secure API access Deliverables Functional web application Source code repository Database schema API documentation Deployment documentation Administrator guide User guide Ownership and Intellectual Property All work product, source code, documentation, specifications, workflows, business logic, prompts, training materials, and derivative works developed under this project shall be deemed works made for hire and shall be the sole and exclusive property of the Client. Contractor shall assign all intellectual property rights to the Client upon creation. Contractor shall not reuse, disclose, distribute, or commercialize any portion of the work product without the Client’s prior written consent.

We are looking for an experienced AI trainer / speaker to deliver a 2–3 hour live, remote Introduction to AI training session for a B2B field sales team The audience will be group of sales professionals. The client is in the protective packaging and packaging automation industry. Their sales team works with customers on packaging materials, packaging processes, damage reduction, labor efficiency, sustainability, throughput, and automation-related opportunities. The goal of the session is to provide a practical and engaging introduction to AI usage in sales workflows. This should not be a highly technical AI course. The focus should be on helping sales professionals understand how AI can support their daily work and improve sales productivity. Desired session focus: Practical introduction to AI and generative AI for non-technical sales users How field sales teams can use AI safely and effectively AI for account research and customer meeting preparation AI for improving discovery questions and understanding customer pain points AI for writing better follow-up emails, summaries, and sales messaging AI for preparing customer-specific value propositions AI use cases relevant to B2B consultative sales Responsible AI use, including confidentiality, accuracy, and human review Live examples and practical demonstrations The ideal trainer should be able to make the session engaging, practical, and relevant to a sales audience. Experience training sales teams, B2B commercial teams, or business users on AI adoption is strongly preferred. Experience in manufacturing, packaging, industrial sales, logistics, automation, supply chain, or similar B2B industries would be a strong plus, but is not mandatory if the trainer can tailor examples appropriately. Trainer responsibilities: Prepare and deliver a 2 hour session Tailor examples to a B2B field sales audience Include practical AI demonstrations that sales professionals can relate to Explain AI concepts in simple business language Provide guidance on safe and responsible use of AI tools Keep the session interactive and engaging for the group Coordinate with us in advance to align the session with client goals Ideal candidate qualifications: Strong experience delivering AI, generative AI, or digital productivity training Comfortable presenting to business and sales audiences Ability to explain AI concepts without unnecessary technical complexity Strong communication and facilitation skills Experience with tools such as ChatGPT, Microsoft Copilot, Claude, Gemini, or similar AI platforms Ability to tailor training examples to client-specific business scenarios Prior experience with sales enablement, B2B sales workflows, or customer-facing teams is preferred Please include the following in your response: Brief summary of your AI training experience Examples of similar business or sales-focused AI sessions you have delivered Your approach for making a 2–3 hour AI session practical and engaging Any relevant industry experience with B2B sales, manufacturing, packaging, logistics, supply chain, or automation Your availability in August for this training session

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

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

We are looking for a skilled Full-Stack Developer with experience in AI and software engineering to support client communication and technical requirement gathering. In this role, you will be responsible for engaging directly with stakeholders through calls, understanding their technical and business needs, and accurately translating those requirements into clear, actionable documentation for the development team. The ideal candidate should have a strong technical background in full-stack development, AI systems, and modern software architecture, enabling them to ask the right questions, validate assumptions, and ensure that project requirements are correctly captured without ambiguity. You will act as a bridge between clients and engineering teams, ensuring smooth communication and reducing misunderstandings during project execution. Responsibilities include conducting requirement-gathering calls, clarifying technical specifications, documenting system needs, and collaborating closely with developers and product teams. Strong understanding of AI-driven systems, web technologies, and software development workflows is essential to perform effectively in this role. We are seeking someone who can combine technical expertise with clear communication skills, ensuring that complex requirements are translated into structured, developer-ready specifications that support successful project delivery.