AI Automation Engineer – Personal Injury Law Firm (Phase 1) Overview We are a plaintiff personal injury law firm seeking an experienced AI automation engineer to build a practical AI-powered operations system that reduces administrative workload and improves case management. Firm Profile: - 1 Attorney - 1 Legal Assistant - Approximately 100 Active Cases - Approximately 25 Cases in Litigation We are not looking for chatbots, prompt engineering, or marketing automation. We are seeking a builder who can deploy production-grade workflow automation integrated with our existing systems. --- Existing Technology Stack - CASEpeer - Supio - Gmail (Google Workspace) - Google Calendar - Google Drive - Claude - ChatGPT - CoCounsel - PLAUD --- Phase 1 Objective Build a Daily Case Command Center and Follow-Up System. The goal is to ensure that every morning the attorney knows exactly which files require attention and why. --- Deliverable #1: Daily Case Command Brief Generate a daily briefing containing: Litigation Matters - Upcoming depositions - Discovery deadlines - Hearings - Expert deadlines - Outstanding litigation tasks Pre-Litigation Matters - Treatment complete but no demand - Missing medical records - Records requests outstanding more than 21 days - Demands pending more than 30 days - Settlement checks outstanding Communications - Unanswered client emails - Unanswered adjuster emails - Unanswered defense counsel emails - Communications requiring attorney attention Case Velocity - Stale files - Cases with no recent activity - Recommended next actions --- Deliverable #2: Gmail Intelligence The system should: - Monitor designated Gmail inboxes and labels - Identify case-related emails - Extract action items - Detect deadlines - Identify follow-up opportunities - Draft suggested responses --- Deliverable #3: Follow-Up Automation Generate draft communications for approval: - Medical records requests - Provider follow-ups - Adjuster follow-ups - Client status updates - Scheduling communications No communication should be sent automatically. Human approval is required before sending. --- Deliverable #4: Calendar & Reminder Automation Create and manage: - Follow-up reminders - Litigation reminders - Discovery reminders - Records request reminders - Suggested calendar events --- Deliverable #5: CASEpeer Integration Where supported by available integrations/APIs: - Create tasks - Create notes - Associate communications with matters - Maintain activity history --- Technical Requirements Required: - n8n - Python - OpenAI API - Anthropic API - Gmail API - Google Calendar API - Google Drive API - REST API integrations Strongly Preferred: - LangGraph - LangSmith - Google Workspace administration - Salesforce integrations - CASEpeer, Clio, or Filevine experience - Legal technology experience - HIPAA or regulated-data experience --- Security Requirements - Human approval before external communication - Activity logging - Error handling - Retry mechanisms - Secure credential management - Documentation of workflows --- What Success Looks Like The system should: - Reduce administrative workload - Improve follow-up consistency - Reduce stale files - Improve litigation oversight - Improve case visibility - Provide a daily prioritized action plan --- Application Requirements Please include: 1. Similar workflow automation projects you have completed. 2. Experience with n8n and AI workflow automation. 3. Experience integrating Gmail and Google Workspace. 4. Experience integrating CRM or case-management systems. 5. Proposed architecture for this project. 6. Estimated timeline. 7. Estimated fixed-fee budget. Begin your application with: CASECOMMAND Applications without this keyword will not be considered. --- Budget Expected Phase 1 Budget: $8,000–12,000 Preference will be given to candidates who can demonstrate production deployments rather than proof-of-concept or prompt-engineering projects.

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.

We are seeking an experienced freelancer to audit our automated lead follow-up system. The ideal candidate will have a strong background in AI automation and be able to evaluate the effectiveness of our current system. Responsibilities include identifying areas for improvement and providing actionable insights to enhance performance. If you have a passion for AI and a keen eye for detail, we would love to hear from you!

I am seeking an experienced ML engineer to provide insights on the design of a model I am planning to build. Your expertise in model design and architecture will be invaluable in helping me make informed decisions.

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

EroFlow Intelligence is an enterprise-grade, autonomous AI orchestration pipeline designed to mitigate global supply chain disruptions for aerospace manufacturing. Built using a multi-agent framework, the system automates the entire lifecycle of risk detection, impact analysis, and procurement mitigation without requiring human intervention for standard operational anomalies. The architecture coordinates three specialized, asynchronous AI agents that communicate via a centralized event bus to solve complex logistical bottlenecks in real-time. Core Agent Architecture & Workflow 1. The Sentinel Agent (Data Ingestion & Extraction) Role: Continuous Global Monitoring. Function: Utilizes advanced LLM-driven web scraping and unstructured data extraction to monitor global news feeds, geopolitical shifts, weather anomalies, and shipping port telemetry. Trigger: If it detects a disruption (e.g., a port strike or critical mineral shortage), it extracts key entities (materials affected, estimated delay times) and passes a structured JSON payload to the orchestration layer. 2. The Impact Assessment Agent (Predictive Modeling) Role: Deep Cross-Referencing & Analytics. Function: Upon receiving a trigger, this agent cross-references the disrupted material with the company’s internal ERP (Enterprise Resource Planning) database and current inventory levels. Output: It runs a predictive analysis to determine exactly which production lines will stall and calculates the financial risk, assigning a high/medium/low priority score to the event. 3. The Mitigation & Logistics Agent (Autonomous Execution) Role: Operational Resolution. Function: If the risk score exceeds a specific threshold, this agent is authorized to take action. It autonomously queries pre-vetted alternative suppliers via APIs, negotiates standard volume pricing based on historical contract data, drafts a comprehensive procurement proposal, and queues the purchase order for final human sign-off (or executes it automatically if under a certain dollar cap). Technical Stack (The Blueprint) Frameworks: LangGraph / CrewAI (for multi-agent state management and deterministic routing). Core Language: Python 3.11+ Data Layer: PostgreSQL (for ERP syncing) & Pinecone / Qdrant (Vector database for storing and querying supplier contract PDFs and historical compliance documentation). LLM Orchestration: OpenAI GPT-4o / Anthropic Claude 3.5 Sonnet utilized via structured outputs (Pydantic parsing) to ensure strict API data integrity. Hosting & DevOps: Containerized via Docker, orchestrated via Kubernetes, and deployed on AWS with asynchronous task queues managed by Celery and Redis. Quantifiable Business Results (The Hook) 92% Reduction in supply chain anomaly response time (from 48 hours down to 14 minutes). Automated Recovery: Successfully mitigated over 140 potential production line stalls autonomously in simulated stress tests. Cost Efficiency: Saved an estimated $1.2M in expedited shipping fees by predicting bottlenecks 10 days before they impacted manufacturing floors.

I'm a retired entrepreneur and active investor looking for a skilled Claude AI practitioner to serve as a private tutor and advisor. I use Claude regularly and have a working Microsoft 365 integration in place, but I want an experienced guide to help me unlock advanced capabilities and build efficient, reusable workflows tailored to my work. This is not a beginner engagement. I learn quickly, prefer direct feedback over hand-holding, and want sessions focused on my actual use cases — not generic training. Topics to Cover - Claude Projects — structure and strategy for ongoing, organized work - Investment and general research — synthesizing company, market, and topic information efficiently - Correspondence — drafting polished emails in Outlook that match my voice with minimal editing - Document analysis — extracting key information from legal, financial, and fund documents - Microsoft 365 add-ins — what's available and genuinely useful for Word, Excel, and PowerPoint - Voice input and dictation — getting started and optimizing as a primary input method - Workflow building — creating persistent, reusable tools rather than starting from scratch each session - Agents, skills, and connected tools — connecting external tools, leveraging agentic capabilities, and building autonomous workflows - Prompt craft — advanced techniques applicable across all of the above Ideal Candidate - Hands-on experience with Claude (not just ChatGPT or general AI) - Background working with business operators, investors, or executives — not primarily developers or academics - Can demonstrate real-world applications, not just theoretical knowledge - Comfortable moving at a fast pace and adapting sessions to my priorities Format Virtual sessions via video call, 60–90 minutes each. Frequency to be determined based on fit and progress. Looking to begin with 4–6 sessions and reassess. To Apply Please include: 1. A brief description of your hands-on experience with Claude specifically 2. One or two examples of business or executive use cases you've worked on 3. Your availability and hourly rate A short introductory call before committing to paid sessions is expected.

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 seeking a skilled GenAI engineer to work with our client in a remote or Chicago-based capacity. The ideal candidate will have experience in developing and implementing AI solutions, with a strong understanding of machine learning and data analysis. Responsibilities include designing AI models, integrating AI into existing systems, and collaborating with cross-functional teams to enhance AI capabilities. If you have a passion for AI and a proven track record in delivering innovative solutions, we would love to hear from you.