Go-To-Market AI Engineer Needed: Multi-Agent System, Dashboard, Automations & GTM Workflows

Overview I’m looking for a hands-on AI engineer to work directly with me for an intensive 4–8 hour paid sprint to audit, debug, and help get a multi-agent go-to-market system working cohesively. We have already built most of the core pieces: multiple specialized agents, agent instructions, handoff triggers, cron logic, workflow rules, an MVP dashboard, and operating logic for a “40 meetings/month” outbound engine. The issue is that the system is not yet working together cleanly end-to-end. The goal of this first engagement is to work live with me, understand the current architecture, identify what is broken or disconnected, and help create a clear path to make the system operational. If it goes well, this can become ongoing work because I plan to productize this system and help other companies build similar AI-powered GTM systems. What the System Does The system is designed to support an outbound revenue engine that can consistently generate qualified meetings. It includes agents/workflows for: Company universe expansion and scraping ICP qualification and lower-middle-market company filtering Contact enrichment and validation Campaign readiness checks Outreach campaign monitoring Reply monitoring and retargeting Signal intelligence and company trigger tracking Dashboard/reporting for campaign health, pipeline, pending volume, and agent status Agent-to-agent handoffs, cron jobs, and task triggers We are not starting from zero. The agents, logic, prompts, and rules already exist. I need someone technical who can help audit the actual system, connect the pieces, and make it reliable. First Project Scope: 4–8 Hour Intensive Sprint For the first sprint, I want to work closely together over Zoom/screen share. The ideal outcome from the first session: Audit the current agent stack, dashboard, automations, and workflow architecture Identify what is working, what is broken, and what is missing Debug any obvious issues preventing the system from running cohesively Review cron jobs, triggers, handoff logic, and agent memory/instruction structure Help create a prioritized technical roadmap for getting the system fully operational Recommend the right architecture for scaling this into a repeatable GTM AI system If possible, make immediate fixes during the working session Technical Areas Involved Relevant experience may include: AI agent systems and workflow orchestration OpenAI API / ChatGPT / Codex-style workflows Multi-agent architectures Cron jobs, background workers, and task scheduling Dashboard/backend debugging Browser automation or agent-based web workflows CRM / outbound / sales automation systems APIs, webhooks, and data pipelines Clay, Apollo, HubSpot, HeyReach, Google Sheets/Drive, Telegram bots, or similar tools Python, TypeScript, Node.js, Next.js, Supabase, Postgres, or similar stack experience Logging, monitoring, debugging, and reliability improvements You do not need to know every tool listed above, but you should be strong at quickly understanding an existing system, identifying failure points, and helping turn a messy MVP into a reliable operating system. Who I’m Looking For I’m looking for someone who is more than a prompt engineer. I need a practical AI engineer / automation engineer who understands how to connect AI agents to real business workflows. You should be comfortable with: Auditing an existing codebase or agent stack Working live with a founder/operator Asking sharp questions and identifying system bottlenecks Turning unclear workflows into clean architecture Debugging integrations and automation flows Thinking about reliability, handoffs, logs, permissions, and failure recovery Helping design something that can later be reused for other companies Nice to Have Experience building GTM, sales, outbound, or revenue automation systems is a major plus. Examples: AI SDR systems Signal-based outbound systems CRM enrichment workflows LinkedIn/email campaign infrastructure Multi-agent business operations systems Dashboards for sales operations or revenue teams Deliverables for First Sprint At the end of the first session, I want: A clear diagnosis of the current system A list of the highest-priority fixes A recommended architecture or system map Any quick fixes that can be made during the session A clear next-step plan for turning this into a reliable, scalable GTM AI operating system Engagement Structure This will start as a paid 4–8 hour working sprint. If it goes well, there will likely be ongoing work helping me: Harden the system Improve the dashboard Add monitoring and logging Build better handoff flows Productize the system for other companies Create repeatable AI GTM infrastructure To Apply Please include: A short summary of your experience with AI agents or automation systems An example of a complex workflow, agent system, or automation stack you have built or debugged What stack/tools you are strongest with Whether you are available for a 4–8 hour live working session How you would approach auditing a partially built multi-agent GTM system Please do not send a generic AI-generated proposal. I’m looking for someone who can think clearly, move fast, and help turn an existing MVP into a working system.