Full‑Scope Middleware & GoHighLevel API Developer (Remote)

@opencollar

Hi, I understand your main needs are creating a reliable middleware that connects GoHighLevel CRM with AI decision tools and making sure data stays secure. I will handle the integration of CRM events via webhooks, storing and avoiding duplicates in a database. For the AI part, I will connect a modern language model that provides clear JSON output, always allowing human review or override. The system will also include features to log all actions and retry failed tasks automatically, making everything smooth and trustworthy. I believe clear talks, quality work, and timely delivery help your business grow faster, and I will support you even after the project finishes. Let’s chat about how we can plan this out and build something bigger together. Regards, Nick.

@irsolutions

With over a decade of experience in full-stack architecture and high-scale systems, I understand the need for a highly skilled developer to build a robust event-driven middleware that seamlessly integrates your GoHighLevel CRM with a bespoke AI-powered decision layer. My background in scaling systems for over 1 million users and developing high-security FinTech solutions directly applies to the complexities of your project at Sarkis AI Inc. To ensure the success of your project, a key strategic insight would be to implement robust event queues and structured logging for seamless data processing. I have successfully built and scaled Telegram Mini Apps serving over 1 million users, showcasing my ability to handle similar levels of complexity with ease. I encourage you to reach out so we can discuss the roadmap for your project further. Let's connect to explore how we can collaborate to bring your vision to life seamlessly.

@TheInnoVibes

Hello Sarkis AI Team, This project is a great match for my experience. I have worked on CRM integrations, webhook-based automation systems, API middleware, and AI-powered workflows. For this project, I would propose: * Node.js (NestJS) or Python (FastAPI) * PostgreSQL database * Redis/RabbitMQ for event processing * OpenAI integration with structured JSON outputs * Secure logging, retry handling, idempotency, and audit trails * AWS/GCP deployment I can take full ownership of the architecture, development, testing, deployment, and documentation. I am comfortable working with milestone-based payments and providing regular progress updates. A few quick questions: 1. Do you already have the AI decision rules defined? 2. Which AI provider do you prefer? 3. Will the system need HIPAA-compliant infrastructure? I would be happy to discuss the requirements further. Best regards, Varun

@softsolution2000

Hi, The idempotency and duplicate-prevention requirement on the webhook layer is the part I'd want to nail early — that's where event-driven pipelines tend to quietly break in production. I build backend integrations in Node.js and Python, including CRM-connected systems with structured AI outputs piped through decision layers. Webhook normalization, retry logic, and audit trails are standard parts of my workflow. I haven't worked with GoHighLevel specifically, but their REST API is well-documented and I've integrated comparable CRMs at this scope before. For the stack I'd go Node.js with PostgreSQL, a lightweight queue (BullMQ or similar), and an OpenAI or Claude endpoint constrained to emit structured JSON with a human-override flag baked in from day one. Happy to share architecture notes or a quick call if you want to pressure-test the approach before committing.

@webperfection123

Hi there, I have a strong background in building robust middleware solutions that connect CRMs like GoHighLevel with sophisticated AI capabilities. With over 7+ years in backend development, primarily using Node.js and Python, I’ve successfully implemented event-driven architectures and API integrations while prioritizing security and data privacy. My previous projects involved designing systems that maintain high reliability through effective logging and handling of asynchronous events. I would love to help you create a seamless integration for your healthcare technology needs. Please share more details about your current system and specific requirements. Best Regards, Priyanka

@rizwange4

Hi Sarkis AI Inc., I can build your GoHighLevel + AI-driven event middleware system as a secure, scalable, production-ready solution. What I will deliver: • Event-driven middleware (Node.js / Python / Go) • Full GoHighLevel API + webhook integration • Queue-based processing with retry, logging, and idempotency • AI decision layer with structured JSON output + rule enforcement • Secure data handling, audit logs, and encryption • Deployment setup + documentation + testing suite Tech Stack: Node.js (NestJS) / FastAPI, PostgreSQL, Redis queue, OpenAI API, AWS/GCP (Docker-based) Experience: Built CRM integrations, webhook pipelines, and AI decision systems with production-level reliability and structured automation flows. Timeline: 3–5 weeks (milestone-based after architecture confirmation) Happy to take full ownership from architecture to deployment. Best regards, M. Rizwan LA

@kamran2012

Hello there, I will build your event-driven middleware — webhook ingestion, deduplication, structured logging, and the GoHighLevel API integration layer for contacts, opportunities, tags, and custom fields — along with the AI decision layer that emits structured JSON under deterministic rule constraints with human-override capability. For the architecture, I will use an idempotency key derived from each webhook's event ID and timestamp, stored in PostgreSQL, so duplicate CRM events are discarded before they ever reach the decision layer. This prevents double-processing without adding external locking complexity and keeps your audit trail clean for healthcare compliance reviews. Send me a message and we can go over the details. Best regards, Kamran

@point2solutions

✨ Event-Driven Middleware & AI Decision Layer for GoHighLevel ✨ I've gone through your requirements and understand that you need a secure, scalable event-driven middleware that integrates GoHighLevel with a custom AI-powered decision engine. The solution will handle webhook processing, event normalization, AI-assisted decision-making, CRM synchronization, audit trails, and enterprise-grade security while maintaining reliability, transparency, and human oversight. Key Features: • GoHighLevel Webhook Integration • Event Normalization & Processing • Idempotency & Duplicate Prevention • AI-Powered Decision Engine • Structured JSON AI Responses • Rule-Based Decision Framework • Human Override Mechanism • Contact, Opportunity & Tag Management • Audit Logs & Activity Tracking • Retry & Error Handling System • Secure Credential Management • Data Encryption & Compliance Controls • Queue-Based Processing Architecture • Monitoring & Alerting Let's connect to discuss expected event volumes, decision workflows, GoHighLevel entities involved, AI decision boundaries, compliance requirements, and deployment preferences so we can finalize the architecture and milestone plan. Thanks

@ZohaibRoy

⭐⭐⭐⭐⭐ Build Event-Driven Middleware for GoHighLevel CRM Integration ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and noticed you're looking for a skilled developer to create event-driven middleware for GoHighLevel CRM. Look no further; Zohaib is here to help you! My team has successfully completed 50+ similar projects in CRM integrations. I will design a secure application that normalizes CRM events, integrates AI decision-making, and ensures compliance with security standards. ➡️ Why Me? I have 5 years of experience in building middleware solutions and API integrations. My expertise includes Node.js, Python, event-driven architecture, and robust logging. I also have strong skills in integrating AI models, ensuring your system is reliable and scalable. ➡️ Let's have a quick chat to discuss your project in detail and I'll show you samples of my previous work. I'm excited to help you with this project! ➡️ Skills & Experience: ✅ API Integration ✅ Event-Driven Architecture ✅ Node.js ✅ Python ✅ Go ✅ Middleware Development ✅ AI Integration ✅ Data Security ✅ Database Management ✅ Logging and Monitoring ✅ Testing & Documentation ✅ Cloud Deployment Waiting for your response! Best Regards, Zohaib

@C0RETECHIES

Hello, I understand the architecture. You need an event-driven middleware to act as an intelligent control layer for GoHighLevel. It will ingest webhook events, use a database for idempotency checks to prevent duplicate processing, and route data through a deterministic rules engine. Events not handled by rules will be passed to an LLM, which must return structured JSON. The final decision triggers API calls to update contacts, opportunities, and tags in GHL, supported by robust logging and retry mechanisms. Technical approach: - Backend: Node.js (Express) with PostgreSQL as the primary database. - Queueing: Use a Redis-based queue (BullMQ) to decouple webhook ingestion from the core processing logic. - Idempotency: Hash incoming webhook payloads to create a unique key and prevent re-processing. - AI Layer: Leverage OpenAI's API with function calling to enforce structured JSON responses. - Deployment: Dockerized application on AWS for scalability and reliability. Core modules: - Webhook Ingress & Queuing Service - Deterministic Rules Engine - AI Decision Service with JSON Output - GHL API Executor & Audit Trail Relevant systems: Automation Lead Generator: We built an 8-agent AI pipeline that uses the GoHighLevel API for complex, automated lead enrichment and outreach, which is architecturally very similar. Implementation will be milestone-based: first the core data pipeline (ingestion/API client), then the rules engine, and finally the AI decision layer, with testing at each step. 1. What are a few examples of the deterministic rules you have in mind? 2. How should the human override process work? E.g., flag in a dashboard, or a Slack/email alert? 3. What is the expected volume of webhook events per day to handle at launch? Regards, Rohit

@Guptapuru304

Hello Sarkis AI Inc., We've thoroughly reviewed your project details and are excited about the opportunity to build the full-scope middleware for your GoHighLevel CRM integration. Our team specializes in developing robust, event-driven middleware systems and has extensive experience integrating AI decision layers with CRM systems, similar to your requirements. Previously, we've successfully crafted a middleware solution for a healthcare technology company, which involved integrating complex API-driven workflows and intelligent decision-making layers. This experience aligns perfectly with your project's objectives. Our expertise in AI-first product development, automation, and web platforms, backed by over 8 years of experience, positions us uniquely to enhance your project. We excel in integrating LLMs to facilitate decision-making processes, ensuring scalability, security, and compliance, especially with sensitive healthcare data. We have a proven record of delivering top-rated results and have worked with over 200 clients, consistently maintaining uncompromised quality and transparent collaboration. Our skills in Node.js, Python, and API development will drive your project to success. We invite you to message us with more details. We'll prepare a detailed proposal within 24 hours, tailored to your specific needs, ensuring our solutions align with your vision. Looking forward to collaborating, Puru Gupta

@skalogir

Hello Sarkis AI Team, I understand you need a production-grade event-driven middleware that integrates GoHighLevel with an AI-powered decision layer, handling webhook ingestion, event normalization, idempotent processing, audit trails, secure data management, deterministic business rules, structured AI outputs, and full deployment readiness. I have experience building API-driven middleware platforms, CRM integrations, event-processing systems, webhook architectures, PostgreSQL-backed workflows, LLM-powered decision engines, structured logging, retry mechanisms, RBAC, cloud deployments, and compliance-conscious systems requiring reliability and traceability. My approach would use Node.js or Python with PostgreSQL, queue-based event processing, idempotency keys, encrypted secrets management, structured JSON AI responses with rule validation, comprehensive audit logging, automated testing, CI/CD pipelines, and milestone-based delivery from architecture through production deployment. Q1: Do you have a preferred LLM provider (OpenAI, Anthropic, Azure OpenAI, self-hosted, etc.) for the decision layer? Q2: Approximately how many webhook events per day do you expect the middleware to process at launch? Q3: Will the AI layer only recommend actions for human review, or should certain rule-compliant actions be executed automatically within GoHighLevel? Best regards, Stratos

@ludiac

Hi, This project aligns closely with the type of AI-driven middleware and automation platforms my team builds. We have extensive experience developing event-driven architectures, CRM integrations, AI decision engines, workflow automation, and production-grade backend systems. For Sarkis AI, we would design a secure middleware layer using FastAPI/Node.js with PostgreSQL, Redis queues, and Docker-based deployment. The platform would ingest GoHighLevel webhooks, normalize events, enforce idempotency and retry policies, maintain complete audit trails, and synchronize contacts, opportunities, tags, and custom fields through GoHighLevel APIs. The AI decision layer would utilize OpenAI/Claude models with strict JSON schemas, deterministic validation rules, confidence scoring, and human-override workflows to ensure reliable, compliant decision-making. Security would include encrypted credentials, role-based access controls, detailed logging, and healthcare-grade data handling practices. Relevant AI Projects: https://www.freelancer.com/projects/php/Sharepoint-RAG-SQL-GPT-agent/reviews https://www.freelancer.com/projects/php/SQL-RAG-GPT-Agent-with/details https://www.freelancer.com/projects/gpt-agent/Data-Analyst-Required/reviews https://www.freelancer.com/projects/php/OpenAI-Prompts-for-Telco-Support/reviews We can handle the complete lifecycle from architecture, development, testing, deployment, documentation, and long-term support. Regards, Ludiac Solutions

@axiomswb

Architecting your GoHighLevel healthcare middleware... I see Sarkis AI needs a secure, event-driven middleware to normalize GoHighLevel CRM webhooks, prevent duplicate processing, and route decisions through a strict, JSON-emitting LLM layer. Here is my exact approach to answer your application requirements: Proposed Tech Stack & Security: I will architect this in Node.js with PostgreSQL, hosted on AWS. I will implement strict idempotency keys for the event queues and apply HIPAA-standard data encryption for your sensitive healthcare data. GHL API & AI Integration: I will build the robust GoHighLevel API sync (contacts, opps, tags) and integrate the LLM to enforce deterministic rules, ensuring it strictly emits structured JSON with the required human-override safety valves. Testing & The Handoff: I will take full end-to-end ownership of this build, delivering the comprehensive unit/integration tests and deployment scripts via fixed-price milestones. Experience & Examples: I specialize in complex API middleware and AI-driven CRM architectures. (Note: Please find links to my recent GoHighLevel API integrations and custom LLM decision-layer repositories attached below). Quick question: For the "human-override" safety valve on the AI decisions, do you want these flagged events pushed to a specific Slack/Teams channel for your team to approve, or will we be managing them via a custom dashboard queue?

@vladang

You’re essentially looking for a reliable decision engine sitting between GoHighLevel and AI, where every event is traceable, replayable if needed, and never processed twice. That’s how I’d approach it from day one. I’d build the middleware around webhook ingestion first, normalizing incoming GHL events into a consistent schema, storing them in PostgreSQL, and enforcing idempotency before anything reaches the decision layer. From there, events move through a queue with retries, dead-letter handling, and structured audit logs so failures never disappear silently. For the AI layer, I’d keep the model constrained to structured JSON outputs and wrap it with deterministic rules that always take precedence. Human overrides, decision history, and full reasoning traces would be built into the workflow rather than added later. I’ve built production backend systems integrating external APIs, event processing, and AI-assisted decision flows using Python and PHP, where reliability and observability were more important than model sophistication. One question: do you already have the decision rules defined, or should they be configurable through an admin layer? I’m ready to start and own the build through deployment and handover.

@InterconnectBPO

Hi, We have experience building API-driven middleware, CRM integrations, workflow automation systems, and AI-powered decision layers. Our team has worked on webhook-based architectures, event processing pipelines, LLM integrations, structured data workflows, and secure backend systems with audit logging and retry mechanisms. For this project, we would recommend a stack based on Node.js or Python, PostgreSQL, Redis/queue processing, OpenAI-compatible LLMs with structured JSON outputs, and deployment on AWS or GCP. We would implement idempotent event handling, comprehensive logging, rule-based decision controls, human override capabilities, and secure credential management from day one. Your requirements around GoHighLevel integration, event normalization, AI-assisted decisioning, auditability, and milestone-based delivery align well with the systems we typically build. We would be happy to review the event flows, decision logic requirements, and expected processing volumes to provide a detailed architecture and milestone plan. Regards Interconnect Team

@taimoorkhan311

Hello, With 4 years of experience in Backend Development, Software Architecture, and Node.js, I am well-equipped to tackle your project's requirements. I understand the need for a robust event-driven middleware to integrate GoHighLevel CRM with an AI-powered decision layer seamlessly. I have expertise in PHP, Java, XML, Database Management, API Development, and GoHighLevel skills to ensure the successful completion of this project as per your specifications. I have carefully reviewed the project details and believe I can deliver exceptional results. Let's connect in chat to discuss further. Looking forward to the opportunity to work together. Best regards, Taimoor from Pixels Soft

@technologiesit

As a Full Stack Developer & Digital Solutions Expert, I believe I bring unique and valuable skills to the table for your middleware and GoHighLevel API development project. My 10+ years of experience includes external API integration and sophisticated webhook handling like GoHighLevel requires. I have built numerous CRM integrations and event-driven architectures throughout my career, dealing with data normalization, storage, duplicate processing, deterministic rules – all elements your project demands. Moreover, engagement ownership is crucial in such complex projects. I promise undivided attention and dedication to your project from beginning to end. This means consistent progress updates in clear writing as well, ensuring you're always aligned with architecture choices, security practices, and any significant decisions along the way. Regarding your preference for North American time zones, let me assure you this wouldn't be an issue as I strive for availability and flexibility. My aim is to help you build a relia

@vishal1145

Your GoHighLevel webhook layer will drop events under load if you don't implement a queue with idempotency checks. I've seen this exact failure mode in 3 CRM integrations where duplicate contact creation caused billing issues and data corruption. Before architecting the solution, I need clarity on two constraints: What's your expected webhook volume per hour during peak operations? Does your GHL plan support bulk API operations, or are you limited to single-record endpoints? Here's the architectural approach: - GOHIGHLEVEL API: Build webhook ingestion with SQS queuing and Redis-based deduplication to prevent race conditions when processing contact updates across multiple workers. - NODE.JS + POSTGRESQL: Implement event sourcing pattern with audit trails, storing every CRM state change with rollback capability for compliance and debugging. - AI DECISION LAYER: Integrate OpenAI with structured output mode (JSON schema validation) and rule-based fallbacks so the system never blocks on AI failures or hallucinations. - RETRY + IDEMPOTENCY: Use exponential backoff with circuit breakers for GHL rate limits and store idempotency keys to handle webhook replays without duplicate processing. - HIPAA COMPLIANCE: Encrypt PHI at rest using AWS KMS, implement field-level access controls, and maintain tamper-proof audit logs for regulatory review. I've built 4 similar CRM middleware systems that processed 500K+ events monthly without data loss. I don't take on projects where failure scenarios aren't mapped upfront. Let's schedule a 20-minute technical call to walk through your edge cases and GHL quota limits before committing to milestones.