[HIRING] Technical AI Automation Specialist — Long-Term Team Collaboration

Jobs
141

Hi Ahmed — I’m interested in the long-term technical side of what you’re building.

My strongest skills are API/webhook integrations, AI-agent orchestration, Supabase/Postgres, workflow reliability, error/retry handling, monitoring, deployment, and connecting multiple systems into one operational flow.

n8n: I’m actively working with n8n-style workflow architecture and integrations, but I don’t want to claim years of client-specific n8n history. My deeper production experience is in custom API/webhook/database automation and AI orchestration.

Retell / Vapi / Twilio: I have not shipped a client voice stack with these specific tools yet. I’m comfortable integrating APIs and telephony-style event flows, but I’d rather prove that with a paid pilot than overstate prior experience.

Three relevant systems I have personally worked on:

  1. HiHiro Center — a central control plane for AI workers with provider routing, Supabase state, approvals, monitoring, retries and self-healing execution.
  2. Hiro Radar — automated opportunity discovery/verification with evidence, scoring, lead routing and operational follow-up.
  3. Hiro Operator — a controlled browser/task execution layer with persistent sessions, owner approvals, audit trails and security boundaries.

For an AI receptionist similar to your example, I would estimate roughly 7–10 working days for a focused production-ready v1 with one CRM/calendar path, human handoff, logging and failure handling; broader hardening/integrations can extend that.

Working model: project-based or ongoing technical partner.
Rate: flexible by scope; for hourly work, roughly $20–30/hr to start.
Availability: can start immediately on a small paid pilot.
Timezone: UTC+4.

If the first delivery meets your standards, I’m interested in staying with the agency long-term as client volume grows.

142

Hi Ahmed — I run OnMode AI from Spain. I’m interested in the long-term technical-partner model, and I want to be precise about my current proof rather than overstate it.\n\nStrongest skills: Make.com, REST APIs/webhooks, data validation, deterministic routing, idempotency/deduplication, persistence, error handling, monitoring, and reliability-focused workflow design.\n\nCurrent hands-on proof (internal/synthetic, not client deployments):\n• Built and tested an authenticated intake/data-plane flow for client/lead/appointment/event payloads, including invalid-auth rejection, validation gates, deduplication, repeated execution and concurrent duplicate-lead tests.\n• Built a Make scenario health monitor covering 16 active scenarios, incomplete executions and state classification; its local test suite currently has 20 passing tests.\n• Tested recovery/operational edge cases around execution history and API-rate limiting, and kept failed/recovery evidence rather than presenting only happy-path runs.\n\nn8n: I’m early-stage and do not claim production n8n client experience yet.\nRetell / Vapi / Twilio: no production proof yet, so I won’t pretend otherwise. I am comfortable working from API/webhook contracts and learning a specific stack against a paid acceptance test.\n\nWorking model: I’d prefer a small paid trial first, then ongoing project-based work if the fit is good. Initial rate: €35/hour, or a fixed-price milestone when scope/acceptance criteria are clear.\nAvailability: project-based / part-time, Europe (CEST), with exact weekly capacity agreed before each assignment.\n\nFor an AI receptionist like your example, my rough engineering estimate would be ~5–7 working days for a bounded v1 after the telephony/CRM/calendar requirements are fixed, and roughly 2–3 weeks for a production-ready version with failure handling, monitoring, human handoff, documentation and acceptance testing. I would not commit that estimate until the provider/account constraints are verified.\n\nIf this level of transparency fits what you’re building, I can share a sanitized engineering proof brief and start with one paid Make/API/CRM workflow so you can judge the work before either side commits long-term.

143

Hi Ahmed,

1. Short introduction
My name is Sergei and I’m based in Germany. I’m currently building AI automation systems for customer communication, lead handling, appointments and business processes. I’m interested in long-term collaboration and I’m happy to start with a small paid task.

2. Strongest technical skills
Python, FastAPI, PostgreSQL, Docker, REST APIs, Webhooks, OpenAI/LLM integrations, Twilio, Telegram integrations, backend automation, testing and debugging.

3. n8n experience
I’m currently developing my n8n skills as part of my automation stack. I want to be transparent: I’m not yet an n8n expert. My stronger experience is backend/API automation.

4. Retell / Vapi / Twilio
I work with Twilio in my own AI receptionist project. I have not yet worked professionally with Retell or Vapi, but I’m comfortable working with API-based platforms and learning them quickly.

5. Projects I have been building
ZELARUNO — a multi-tenant AI receptionist platform for small businesses with voice and messaging, lead collection, appointment workflows, multilingual interaction, OpenAI integration and telephony.

Program Factory — an AI-assisted software production system with structured requirements, reusable components, automated testing and validation.

6. Demo / screenshots
ZELARUNO is still under active development. I can provide screenshots or a private demonstration of the current system.

7. What I personally handle
Backend development, API integrations, database structure, Docker deployment, OpenAI and Twilio integration, workflow logic, testing and debugging.

8. Rate
I’m open to a small paid fixed-price test task first. For ongoing work, approximately €25–30/hour, depending on scope.

9. Preferred model
Remote, project-based or ongoing part-time collaboration.

10. Availability
I can start with a small task immediately.

11. Timezone
Germany — Europe/Berlin.

12. AI receptionist delivery estimate
For a clearly defined production-ready first version with telephony, lead qualification, appointment booking, integrations, error handling and deployment, approximately 4–8 weeks, depending on requirements. A smaller MVP could be delivered earlier.

I prefer to be transparent about what I already know and what I’m still learning. Your AI receptionist work is particularly relevant to me because it is very close to the system I’m already developing.

Best regards,
Sergei

144

Hi Ahmed, I’m Drilon, a Germany-based full-stack developer focused on TypeScript/Node.js, n8n/Make-style workflow orchestration, REST/webhooks, OpenAI APIs, and PostgreSQL/Supabase. I personally build integrations with validation, retries, logging, and clear documentation rather than only coordinating others. I’m interested in a long-term collaboration, while being transparent that I’m not claiming a large agency or insurance-specific track record. Happy to start with a scoped workflow review and discuss the team’s current priorities. Best, Drilon

145

Hi! I’m interested in the long-term collaboration.

I’m currently building AI automation systems mainly with Make.com, OpenAI, APIs/webhooks and Telegram. My strongest area is lead handling automation: AI conversations, qualification, collecting customer details, workflow state, follow-up logic, notifications and human handoff.

My current experience:

  • Make.com — my main automation platform
  • OpenAI / LLM integrations
  • REST APIs and webhooks
  • Telegram bot automation
  • Lead qualification and routing
  • Data storage and workflow state
  • Human handoff and manager notifications

I’ve personally built a LeadFlow AI system where incoming leads interact with an AI assistant, the system collects location/service/booking information, maintains conversation state, qualifies the lead, and then hands the complete lead information to a manager.

I’m currently expanding into n8n. I don’t yet have production experience with Retell/Vapi/Twilio, so I don’t want to overstate that experience, but AI receptionist and lead-handling systems are exactly the direction I’m developing in.

I can share a demo of my current LeadFlow project.

For compensation, I’m flexible and would prefer to agree on a fixed price per project initially, based on scope. I’m available to start with a smaller paid project/test and grow into ongoing collaboration.

Timezone: UTC+3. I prefer written communication for project discussions.

For a full production-ready voice receptionist, I’d want to review the exact integrations and requirements before giving a reliable delivery estimate rather than promise an unrealistic timeline.

146

Hi Ahmed,

  1. Intro: I’m Haris, an AI automation engineer (5+ years) based in Pakistan. I build production voice receptionists, CRM automation and multi-agent systems for US, UK and AU clients.
  2. Strongest skills: n8n (expert), voice AI (Retell, Vapi, Twilio), Supabase/Postgres, FastAPI, Next.js, Python, Claude/OpenAI APIs, MCP servers, RAG.
  3. n8n experience: 5+ years. Complex production workflows with error branches, retries, input validation, logging and alerting. Self-hosted and cloud.
  4. Retell / Vapi / Twilio: Built and deployed live AI receptionists that handle inbound calls, book appointments, sync to CRM and send SMS confirmations through Twilio. Covered call flows, function calling, webhooks and number provisioning.
  5. Projects I built: (a) Multi-tenant SaaS CRM + AI receptionist for a US barbershop (Twilio, voice AI, Supabase, Next.js); (b) Multi-agent AI automation platform for a fintech client; (c) AI voice receptionist outreach system for US med spas.
  6. Links: https://theharisai.com | https://www.youtube.com/@harisailab | Loom walkthrough on request
  7. What I personally handled: Full ownership, from architecture, voice agent prompt and call flow, n8n backend, database and dashboard through deployment, monitoring and client handover.
  8. Rate: $35/hr, or $1,200 fixed for a production-ready AI receptionist.
  9. Working model: Long-term contractor. Fixed price per build plus a monthly retainer for maintenance and monitoring.
  10. Availability: 25-30 hrs/week, can start immediately.
  11. Timezone: PKT (UTC+5), with overlap for EU mornings and US East.
  12. Production AI receptionist: MVP in 5-7 days (call flow, booking, CRM sync, SMS). Fully production-hardened with edge cases, failover, monitoring and testing in 2 weeks.
    Happy to do a quick call or a small paid trial.

Haris

147

Hi Ahmed,

My name is Adaora Nnaji, and I’m an AI automation workflow builder based in Edmonton, Canada. I’m interested in collaborating with your agency as a Technical AI Automation Specialist and growing with the team over the long term.

  1. Short introduction

I build end-to-end AI automation systems using n8n, LLMs, APIs and business applications. My background also gives me practical experience understanding customer communication, sensitive information and the importance of dependable processes.

  1. Strongest technical skills

• n8n workflow design and automation
• OpenAI and Google Gemini integrations
• REST APIs and webhooks
• Structured AI outputs and data transformation
• Google Sheets, Gmail, Google Drive and Slack integrations
• Automated reporting and notifications
• Prompt engineering
• Workflow testing and troubleshooting
• Data validation, conditional routing and error handling

  1. Experience with n8n

I have practical experience building complete n8n workflows that receive data, process it with AI, connect with APIs, update business records and deliver notifications or reports.

I have worked with webhook and form triggers, HTTP Request nodes, AI agents, structured-output parsers, Google Workspace, Slack and external data APIs. I have also resolved authentication, field-mapping, API-response, model-compatibility and data-formatting errors.

  1. Experience with Retell, Vapi and Twilio

My strongest hands-on experience is currently with n8n, LLMs, APIs and business-process automation. I have not yet deployed Retell, Vapi or Twilio for a paying client, so I do not want to overstate my experience.

I am currently developing my voice-automation skills and understand the architecture required to connect a voice agent with n8n, calendars, CRM systems, lead qualification, notifications and human handoff.

  1. AI automation projects I personally built

Customer Enquiry and Support Ticket Automation

I built an end-to-end system using n8n, Tally, OpenAI/Gemini, Google Sheets, Gmail and Slack. It receives customer enquiries, classifies them, creates structured support records, sends acknowledgements and alerts the appropriate team.

Multi-Agent Market Research and Report Generator

I built an n8n system with separate research agents using PubMed, World Bank and NewsAPI data. It includes a quality-review agent, report-generation agent and automated Slack delivery.

Pharmacy Operations Assistant and Weekly Reporting System

I built a workflow that processes invoice, payment, expense, payroll and operational-task data. It identifies outstanding balances and critical tasks, generates structured reports and produces scheduled executive summaries.

  1. Portfolio links

Portfolio:

LinkedIn:

https://www.linkedin.com/in/adaora-nnaji-415a08231

Additional workflow screenshots and demonstrations can be provided upon request.

  1. What I personally handled

I personally designed the workflow architecture, configured the nodes and integrations, developed the AI prompts, mapped and transformed data, implemented validation rules, tested different scenarios, diagnosed errors and documented the completed workflows.

  1. Expected compensation

For initial contract work, my expected rate is approximately USD $25–$30 per hour, depending on the scope and technical requirements. I am also open to fixed-price projects with clearly defined milestones and deliverables.

  1. Preferred working model

I prefer a remote, part-time contract arrangement with the possibility of developing into a consistent long-term collaboration as the agency’s client pipeline grows. I am comfortable with hourly or milestone-based projects.

  1. Availability

I am available for approximately 10–15 hours per week, primarily during evenings and weekends, with some flexibility for scheduled meetings and urgent project requirements.

  1. Timezone

Mountain Time — Edmonton, Alberta, Canada.

  1. Estimated AI receptionist timeline

With clear requirements and access to the required platforms, I would estimate:

• 4–7 days for a functional prototype
• Approximately 2–3 weeks for a production-ready version

The final timeline would depend on the CRM, calendar, telephony provider, call flows and number of edge cases.

A production-ready version would include data validation, API-error handling, retries, human handoff, logging, testing, monitoring and documentation—not only the basic call flow.

Although I am still expanding my direct voice-agent experience, I bring strong n8n, API, LLM and troubleshooting skills. I am reliable, communicative, willing to complete a reasonable technical assessment and interested in building a genuine long-term working relationship.

Thank you for considering my application. I would be happy to discuss your first planned client use case and explain how I would approach its architecture.

Best,
Adaora Nnaji

148

Hi Ahmed,

I’m Ifiok Columba, an early-career AI Automation Engineer based in Lagos, Nigeria (WAT, UTC+1). I build production-style n8n workflows end to end, orchestration, database logic, and the delivery layer, not just connecting nodes, and n8n is my primary tool for that.

I haven’t used Retell, Vapi, or Twilio yet, but the layer around them, intent routing, business rules, and handoff logic, is exactly what I build in n8n, so picking up the voice layer would be a quick add rather than a new skill set.

Three projects show that directly. My AI Scheduling Agent (n8n, MCP, PostgreSQL, Google Calendar, Telegram) handles the full booking/reschedule/cancel flow, with calendar and database tools exposed through a dedicated MCP server rather than hardcoded into the workflow, and business rules enforced with PostgreSQL constraints so double-booking is structurally impossible, with automatic rollback if the database and calendar ever drift out of sync, the same failure class you flagged in your post. My Lead Scoring & Routing Pipeline (n8n, Gemini, Slack, Gmail, Sheets) sanitizes intake, filters duplicates and disposable domains, then combines deterministic scoring with an AI read on intent before routing leads into SLA tiers with Slack alerts. My Invoice Intake & Anomaly Detection pipeline extracts and independently recalculates line-item totals from Gmail, catching discrepancies and filtering alerts so the channel only fires on genuine anomalies rather than every routine invoice. I built and handled all three end to end, architecture, integration, testing, and documentation.

Portfolio with full architecture breakdowns: ifiok-portfolio.vercel.app, GitHub: Jeff5812 · GitHub

On the practical side: I’m looking at $10-15/hour to start, open on rate once scope and responsibility are clearer, available 20-30 hours a week remotely, and genuinely interested in the long-term angle rather than a one-off task. For your receptionist example specifically, I’d rather inspect the actual CRM, telephony setup, and failure/acceptance criteria than guess at a number, but for the orchestration layer alone (intent, qualification, booking, CRM write, notification, handoff, with retries and logging), based on my scheduling agent build, I’d estimate 1-2 weeks. I wouldn’t commit to a voice-layer timeline before a short paid ramp on Retell or Vapi specifically.

Happy to walk through any of these three projects live if useful.

Ifiok

149

Hi Ahmed,

I’m Evan, an Automation & Integration Engineer based in Indonesia (UTC+7). I build n8n-centered systems around APIs, webhooks, PostgreSQL/Supabase, CRM/email operations, and AI-assisted workflows.

My strongest area is not just connecting nodes — it’s making workflows reliable after the happy path: validation, deduplication, retries, explicit failure branches, state handling, logging, and human-review boundaries.

n8n experience
I use n8n for multi-step workflow orchestration, API/webhook integrations, routing, follow-up control, structured data handling, retries, and operational state.

Retell / Vapi / Twilio
I haven’t shipped a production voice-agent stack with Retell, Vapi, or Twilio yet, so I don’t want to overstate that. The surrounding orchestration layer — intent handling, lead qualification, CRM writes, booking logic, notifications, retries, and human handoff — is directly aligned with the systems I already build.

Relevant work I personally built

1. Revenue Operations workflow system
Lead intake, routing, follow-up control, suppression/deduplication, state persistence, retries, CRM/email workflow logic, and human-review boundaries.

2. Production Integration Reference
Public engineering reference showing API/webhook handling, validation, replay-safe processing, testing, CI, debugging, and failure recovery:

3. BIMMCA Intelligence
Supabase/PostgreSQL-backed monitoring workflow and dashboard with structured data flows and AI-assisted processing:

I personally handled the architecture, workflow logic, integrations, testing, documentation, and reliability controls in these builds.

Rate: USD 18/hour to start, or fixed-price for clearly scoped builds.
Working model: remote contract/project work, with interest in long-term collaboration.
Availability: up to 30 hours/week.
Timezone: UTC+7, Indonesia.

For the AI receptionist example, I would not give a defensible “production-ready” timeline before seeing the CRM, calendar rules, telephony setup, failure paths, and acceptance criteria. For the orchestration layer alone — intent → qualification → booking → CRM write → notification → human handoff, with retries and logging — I’d expect roughly 1–2 weeks for a solid first implementation. I’d want a short paid ramp on the voice layer before committing to the full end-to-end production estimate.

If useful, I’d rather start with one small paid workflow or repair task so you can judge how I structure, test, document, and hand over work before discussing anything long-term.

GitHub: naraya07pedro-spec (Evan Naraya) · GitHub
LinkedIn: https://www.linkedin.com/in/evannaraya

— Evan

150

Hi,

I saw your post: “[HIRING] Technical AI Automation Specialist — Long-Term Team Collaboration”

I build exactly this: n8n + Python + AI automation, self-hosted, production-grade.

For your case I’d scope it in 3 short phases:

1. Data/model + auth foundation (no rework later)

2. Core workflow(s) + agent sub-workflows (clean, not a monolith)

3. Ops: logging, alerts, backup/restore runbook + handoff doc

How I work: limited/watermarked demo first, 50% prepay or Kwork-escrow, start within a day.

To size Phase 1 properly I’d like 15-30 min to look at your spec/mockup.

What’s the best way to reach you, and can you share the details?

Best,

Renat Rakimbek

151

Hi Ahmed, I am interested in the long-term version of this, not the one-off task version. My daily work is exactly your scope: customer communication automations, lead handling, appointment booking flows and repetitive process removal, built with n8n, OpenAI agents, WhatsApp and web apps. Recent live builds: a clinic booking assistant answering in under a minute, lead enrichment pipelines, and document automation. I am a full-stack engineer in Morocco GMT+1, US and EU hours both fine. What does the first month of the collaboration look like on your side, and what would you want delivered first?

152

Hi Ahmed,

I’m WASCO, a beginner AI automation developer currently focused on building practical systems with n8n, AI/LLM APIs, webhooks, APIs, Google Sheets/CRM workflows, and Python.

I’m very interested in the long-term opportunity because I’m looking to grow by working on real client systems rather than only building tutorials or isolated experiments.

Strongest technical skills

- n8n workflow development

- Webhooks and REST APIs

- OpenAI/LLM integrations

- AI-based classification and qualification

- Lead generation and lead routing

- Google Sheets / CRM-style data workflows

- Structured AI outputs

- Workflow logic and conditional routing

- Human approval workflows

- Debugging and testing

I’m also learning Python and working toward becoming stronger with databases, deployment, monitoring, and more advanced API integrations.

n8n experience

I have been building practical n8n workflows myself and focusing on the complete workflow rather than only individual nodes.

I think about systems as:

Trigger → Validate/Input → Process → AI decision → Tools/API calls → Conditional logic → Human approval → Action → Database/CRM → Notification → Logging → Error handling

I understand that production automation needs to account for things such as invalid data, API failures, duplicate records, retries, human handoff, and logging.

Projects I’ve built

1. AI Lead Qualification System v1

Lead comes through a form/webhook → AI analyzes and qualifies the lead → result is structured → saved to Google Sheets/CRM → salesperson is notified.

I personally handled the workflow logic, AI qualification, data flow, storage, and notification process.

2. AI Local Prospecting Agent

The system takes a target location → finds local businesses → researches them → evaluates whether there may be a relevant service opportunity → generates personalized outreach → requires human approval before sending → logs the result.

I personally designed the research, qualification, AI processing, personalization, approval, and logging workflow.

3. AI Local Lead Hunter

This is the project I’m currently developing further. I’m taking the prospecting system and making it more reliable and useful as an end-to-end lead-hunting workflow, with better research, qualification, personalization, approval, and tracking.

I can share demos/screenshots/GitHub as they are available.

Retell / Vapi / Twilio

I have not yet built production systems with Retell, Vapi, or Twilio, so I don’t want to claim experience I don’t have.

However, I understand the workflow architecture behind the type of system you described, and I’m actively learning the missing components. I’m comfortable working with APIs, webhooks, AI models, conditional logic, data handling, and n8n, so I believe I can learn the platform-specific parts quickly.

Compensation

I’m flexible at this stage and would prefer to discuss compensation based on the actual responsibilities, project scope, and working arrangement.

My priority is building real experience and contributing useful technical work.

Working model

Remote would be my preference.

Availability

I’m available for part-time/project-based work and can discuss availability depending on the workload and project requirements.

Timezone

Pakistan Standard Time (PKT), UTC+5.

I’m especially interested in the fact that you’re building an early-stage agency. I’d be happy to start with a small technical task or demo so you can evaluate how I work rather than relying only on what I say.

T hank you, and I’d be happy to share my projects and demos.

Best,

[Your Name]

153

Hi Ahmed — I’m interested in the long-term technical collaboration, especially the production-thinking side of your post.

I run CLEAR MERIT in South Korea. My strongest hands-on areas are n8n, REST APIs/webhooks, Airtable/Google Sheets/Gmail integrations, workflow state/data handling, self-hosted n8n/Docker, debugging, duplicate prevention, retries/error paths, human approval/handoff, QA, and documentation.

For transparency: I do not have production client experience yet with Retell, Vapi, or Twilio, so I would not present myself as a ready-made voice-stack specialist. I would rather prove fit on a small paid workflow first and expand after the unfamiliar voice layer is validated.

Things I personally built:

  1. CLEAR MERIT Internal Revenue OS — Gmail → n8n → Airtable with duplicate prevention, autoresponder filtering, state/status branching, suppression gates, human approval, exception handling, and QA/regression checks. This is an Internal / Working Demo, not external client production work.
  2. Public n8n workflow asset — “Send internal due-action alerts from Airtable via Gmail without duplicates”: Send internal due-action alerts from Airtable via Gmail without duplicates | n8n workflow template

What I personally handle: workflow design, n8n implementation, API/webhook mapping, state/idempotency logic, error and retry paths, test cases, Docker/self-hosting, documentation, and handoff.

Rate: USD 20/hour, or preferably one small fixed-scope paid trial first.
Working model: remote, async-first, project-based initially; open to recurring work.
Availability: about 10–20 hours/week initially.
Timezone: KST (UTC+9), with written async communication preferred.

For an AI receptionist like your example, I’d estimate roughly 3–4 weeks for an orchestration v1 after the CRM, calendar, voice provider, booking rules, failure paths, and acceptance criteria are fixed. I would not commit to the production voice/telephony layer until I validate the provider-specific behavior and edge cases.

If useful, send me one bounded client workflow with the expected input, output, failure cases, and acceptance criteria. I’m happy to prove fit through a paid trial rather than asking you to take the whole profile on trust.

— Sil Cheon Kim
CLEAR MERIT

154

Hi Ahmed,

What stood out to me is that you’re looking for someone who can own the reliability of the complete automation system—not just build individual n8n workflows.

That is exactly how we approach automation at RAR 121: workflow architecture, structured AI outputs, API/webhook integration, validation, error handling, testing, data reliability, and human handoff.

We’ve personally built and tested n8n systems covering AI analysis, business logic, structured data, validation, storage, and troubleshooting, with a strong focus on making workflows reliable and maintainable rather than simply making a demo work once.

I’d be happy to share a concise walkthrough of a relevant system and explain the architecture, implementation decisions, and reliability controls behind it.

Best regards,

RAR 121
Comprehensive, Integrated & Powerful AI Business
Growth Ecosystem

155

Hi Ahmed ? I?m interested in the long-term technical role.

Strongest skills: n8n workflow automation, REST APIs/webhooks, CRM and lead-routing logic, Google Workspace integrations, local Ollama/LLM workflows, databases, validation, retries, monitoring, and failure recovery. I?m especially focused on the Build ? Test ? Deploy ? Monitor ? Maintain side of automation.

Relevant work I can discuss:
? A live acquisition/lead-qualification system using n8n-style orchestration, CRM routing, Gmail provider integration, suppression rules, retries and telemetry.
? A local AI/content automation stack using Ollama, FFmpeg, research/quality gates and scheduled workflows.
? Automation integrations using structured data, webhooks, APIs and persistent state with documented recovery paths.

To be transparent, I do not want to claim production Retell/Vapi/Twilio deployments that I cannot evidence. My strongest overlap is the orchestration, API/webhook, CRM, AI-routing, data and reliability layer; I can work from a defined voice/telephony architecture and integrate the required components.

I?m based in India (IST, UTC+5:30), remote, and flexible about overlap. I prefer paid milestone-based work with scope and acceptance criteria agreed before implementation. For a production AI receptionist, I?d estimate the timeline only after reviewing the call flow, telephony provider, CRM, booking rules, and acceptance tests rather than inventing a fixed number up front.

Happy to share concrete workflow details and discuss a first paid milestone.

Regards,
Satya Prakash
AI Automation Studio

156

Hi,

I’m Oseni Lawal, an AI Automation Engineer focused on building practical automation systems and agentic workflows that connect AI with real business processes.

Your post caught my attention because this is exactly the type of work I want to grow into long-term: not just building individual automations, but designing complete systems that can be tested, deployed, monitored, maintained, and improved as the business grows.

1. Short introduction

I specialize in n8n, AI/LLM integrations, APIs, webhooks, data processing, workflow orchestration, validation, routing, notifications, and agentic automation.

My approach is very implementation-focused. I like to start with the business process, map the logic and edge cases, then build the workflow around reliability rather than simply making the happy path work.

2. My strongest technical skills

  • n8n workflow automation

  • AI/LLM integrations and agentic workflows

  • REST APIs and webhooks

  • OpenAI / Gemini / Groq / OpenRouter integrations

  • Airtable / Google Sheets / database workflows

  • Data validation, transformation and routing

  • Conditional logic and multi-step orchestration

  • Email, Slack, WhatsApp and notification automation

  • Error handling, logging and workflow troubleshooting

  • CRM-style business process automation

  • Automation monitoring and failure-response design

I also have experience working with both traditional automation and agentic workflows, including workflows where AI is responsible for analysis, classification, decision support and routing.

3. My n8n experience

n8n is one of my primary automation platforms.

I have built workflows involving forms, databases, email, AI models, notifications, scheduling, routing, validation and multi-stage business logic.

One area I pay particular attention to is what happens when something goes wrong. For example, handling duplicate submissions, failed authentication, API errors, invalid data, failed downstream nodes and notification failures rather than assuming every workflow execution will succeed.

4. Retell / Vapi / Twilio

My strongest hands-on experience today is on the n8n/API/AI orchestration side rather than large production deployments specifically with Retell, Vapi or Twilio.

I do not want to exaggerate that.

However, I understand the architecture required to connect a voice layer to an automation backend: receive the call/event → understand intent → collect and validate information → apply business rules → call external APIs → update CRM/database → schedule appointments → notify staff → escalate to a human when required.

I am actively expanding my practical work in AI voice agents and agent-based systems, so this is an area I am intentionally building deeper expertise in.

5. AI automation projects I personally built

Jendol Inventory Automation
An inventory management and reorder automation designed around operational efficiency.

The workflow collects inventory information, validates and processes it, routes stock conditions, uses an LLM to analyze low-stock situations, looks up supplier information, creates inventory/reorder records, sends supplier communications and alerts the manager.

The important part for me was not just automating data entry, but connecting the entire decision and response chain.

Homelink Real Estate Support Bot
A multi-workflow n8n system designed to support real-estate operations and customer interactions.

I worked with multiple workflow components including property data, availability logic, customer requests, similar-property handling, notifications and calendar/booking-related processes.

The system was designed around an agent-based architecture rather than a single linear automation.

MedFlow Clinic Automation
An appointment and clinic workflow using Tally, n8n, Airtable and Gemini.

The system handles appointment intake, specialty-based routing, record creation, reminders and follow-up automation.

The workflow was designed so that each appointment is handled as a structured record and the automation can move the information through different stages without relying on manual intervention.

6. Demos / portfolio / GitHub

Portfolio: https://my-potfolyo.netlify.app/

GitHub: github.com/lawally-web

Loom / workflow demonstrations: ClinicAI | Loom

I can also walk through the actual workflow logic and explain exactly what I personally built in each project.

7. What I personally handled

For the projects above, I personally worked on the workflow architecture, n8n implementation, AI integration, routing logic, data handling, API connections, notifications, validation and troubleshooting.

I am particularly interested in understanding the complete system rather than owning only one node or one integration.

8. Expected compensation / rate

For ongoing work, I’m currently targeting approximately $12–$20/hour, depending on the complexity and responsibility of the work.

I’m also open to a project-based or hybrid arrangement if that makes more sense for the agency’s early-stage structure.

9. Preferred working model

I prefer a long-term remote collaboration, with clear ownership of technical tasks and communication around requirements, testing, deployment and maintenance.

I’m comfortable with project-based work initially and growing into a more consistent technical role as the agency’s client pipeline develops.

10. Availability

I’m available to begin immediately and can work with flexible hours around project requirements.

11. Timezone

WAT — West Africa Time (UTC+1), Nigeria

12. Production-ready AI receptionist timeline

For a system covering:

Incoming call → AI conversation → intent detection → lead qualification → data validation → appointment booking → CRM update → notification → human escalation

I would estimate approximately 4–7 working days for a solid production-ready v1, assuming the required accounts, API credentials, CRM, calendar and telephony access are available.

A basic MVP/prototype could be developed faster, but I prefer allowing enough time for testing, edge cases, fallback logic, logging and failure handling before calling something production-ready.

Why I think I could be valuable to an early-stage agency

I’m not looking at this as “build a workflow and move on.”

I’m interested in the entire lifecycle:

Understand → Architect → Build → Test → Deploy → Monitor → Debug → Improve

That is also why your emphasis on reliability, human handoff, retries, validation, logging and edge cases stood out to me.

I’m building toward becoming a highly capable automation engineer, and I’m specifically looking for an environment where I can contribute technically while growing alongside a serious early-stage team.

I’m happy to discuss the projects above in detail and demonstrate the workflow architecture behind them.

Best,
Oseni Lawal

157

Hi,

I’m Akash Ahmed, a junior AI Automation & n8n developer from Bangladesh. I’m interested in joining your team for long-term AI automation projects.

My strongest technical skills include:
• n8n workflow automation
• AI Agents and LLM integrations
• REST APIs and Webhooks
• Google Sheets, Google Drive and Gmail automation
• Airtable
• RAG / knowledge-base systems
• WhatsApp automation
• Gemini integrations

I have hands-on experience building different automation systems with n8n. Some of my projects include:

  1. RAG Customer Support Agent
    I built a RAG-based customer support system that uses provided documents/knowledge sources to help an AI agent answer customer questions.

  2. WhatsApp → Google Sheets Automation
    I built a webhook-based workflow that receives WhatsApp customer messages and automatically stores customer/order information in Google Sheets.

  3. n8n AI Agent + Gemini + Webhook
    I built a workflow where a webhook receives a request, sends it to an AI Agent using Gemini, processes the response and returns it through a webhook response.

I personally worked on the workflow design, n8n configuration, API/webhook connections, AI integration, data handling and testing.

I have not yet worked extensively with Retell, Vapi or Twilio. However, I’m comfortable working with APIs, webhooks and AI integrations and I’m willing to learn these tools as required.

Portfolio:

LinkedIn:

I’m looking for a part-time/long-term collaboration and can currently commit around 2–3 hours per day.

Timezone: Bangladesh (UTC+6)

For compensation, I’m open to discussing a suitable rate based on the project scope and responsibilities.

For an AI receptionist similar to your example, I would first review the exact requirements, integrations and expected features before giving a final estimate. Based on the scope, I would expect an initial version to take approximately 3–5 days.

I’m interested in contributing to your team and growing through real client automation projects.

Thank you,
Akash Ahmed

158

Hi Ahmed, is there a current funded client task where you need help with the n8n/API reliability layer? My relevant independent project is CAPC (Cognitive Autonomous Project Corporation), a Human-Governed AI Work Organization, covering webhook intake, routing, approval gates and execution validation. A focused paid test could cover payload validation, duplicate-event handling, a CRM write and a controlled failure/human-handoff path. I am not claiming production Retell/Vapi/Twilio experience. If this slice is useful, could you share a redacted brief, acceptance checks, budget and milestone-funding arrangement? I would assess those before proposing a price or delivery date. Thank you, Yong.

159

Hi Ahmed,

Short introduction: I’m Buseko, based in Lusaka, Zambia. I co-founded a data and automation consultancy, and I build AI voice agents and n8n workflows for real clients, not tutorial projects.

Strongest technical skills: n8n workflow design and production hardening, Vapi voice agents, LLM tool-use (Claude and OpenAI), webhook and REST API integration, WhatsApp Business API, and building things so they fail loudly instead of silently.

n8n experience: this is my main tool. Production systems include a loan reminder and mobile-money collection workflow (dual-channel WhatsApp and SMS, staged reminders at 7, 3, 1 and 0 days), a WhatsApp invoicing system that turns a text message into a tracked PDF invoice, an AI resume screening system with per-role PDF ranking, and a Google Drive to OpenAI embeddings to Pinecone retrieval pipeline.

Retell / Vapi / Twilio experience: four voice agents built and verified end to end on Vapi plus n8n. A dental receptionist with genuine double-booking prevention, a restaurant reservation host, an email reminder assistant, and a bilingual Afrikaans/English holiday-rental agent. One runs in Nyanja using a clone of my own voice. I’ve hit and documented twelve reusable Vapi integration bugs along the way, things like n8n silently dropping Vapi’s function-call arguments and timezone offset mismatches.

Two or three projects I personally built:

1. Dental receptionist voice agent (Vapi + n8n): books, reschedules and prevents double-booking against a real calendar, verified live end to end.

2. WhatsApp RAG agent: Drive ingestion, chunking, OpenAI embeddings, Pinecone vector index, queried by a WhatsApp agent as a callable tool.

3. Loan reminder and collection system: 7/3/1/0-day staged reminders across WhatsApp and SMS, plus MoMo/Airtel auto-collection, hardened to a fifth production version.

What I personally handled: architecture, the n8n workflows, the Vapi agent prompts and tool definitions, the API integrations, and the debugging when Vapi and n8n disagreed with each other, which happened often.

Links: buseko-Actuary (Buseko Fungamwango) · GitHub (public repos include the RAG agent and a data-analysis portfolio). Happy to share Vapi call recordings or a Loom walkthrough on request.

Expected compensation: open to project-based or a fixed monthly retainer once there’s real client work, whichever suits how you’re structuring the team. I’d rather agree it against a specific first project than quote a number in the abstract.

Preferred working model: remote, async-first, comfortable with occasional calls.

Availability: currently a final-year university student, so part-time with flexible hours during the week, can flex up around exams and holidays.

Timezone: Central Africa Time, UTC+2.

Build time for a production-ready AI receptionist like your example: for the complexity you described (intent, lead capture, qualification, booking, CRM update, notification, human handoff for urgent calls), roughly one to two weeks for a first working version, then a few more days of testing against real call patterns before I’d call it production-ready. That estimate comes from having built this shape of system four times already.

Happy to jump on a call.

Buseko

160

Hi, I’m Cedrik, a solo founder in Florianópolis, Brazil (UTC-3). I build WhatsApp automation and AI receptionists and run them in production on my own infrastructure.

Strongest skills: n8n, WhatsApp APIs (Evolution and Cloud API), OpenAI, Supabase/Postgres, TypeScript/NestJS, React Native (Expo), self-hosting on Coolify/Hetzner.

Projects I built myself:

  1. saluta.health: WhatsApp AI receptionist for clinics. The patient writes, the agent works out what they need, collects name, phone and service, and books the appointment in Google Calendar. n8n, OpenAI, Supabase. I built the flows, prompts, database and deployment.
  2. Rapidex: mobile app (Expo) and NestJS/Supabase backend for a logistics company, with WhatsApp in the loop. Over-the-air releases, CI, uptime alerts, and an n8n watchdog that reconnects the WhatsApp instance on its own when it drops.
  3. melho.app: the same ordering and dispatch automation, packaged for transport companies.

n8n: daily, self-hosted, in production (webhooks, retries, error branches, alerting).
Retell / Vapi / Twilio: not in production yet. I’ve built the same flow over WhatsApp text; the voice layer is the part I’d be picking up.

Rate: US$50/h, or a fixed price per build after scoping. I work as a contractor and invoice in USD/EUR through my EU company.
Availability: 20–30 h/week, async-first, written communication preferred.
An AI receptionist like your example: 2–3 weeks for a first production version with logging, retries and human handoff, plus a week of testing on real calls.

saluta.health and melho.app are live; demos on request.