AI Agent Technical Owner
Budget: $8 – $15 USD
he Role
You will be the technical owner of our AI agent ecosystem. We currently run 30+ automated skills and agents through Claude (Anthropic), OpenClaw, and various API integrations (HubSpot, Monday.com, Google Workspace, RingCentral). Your job is to deploy, maintain, improve, and scale these agents — and build new ones as the business needs them.
This is NOT a traditional software engineering role. You will be working with AI agent frameworks, prompt engineering, API integrations, automated email systems, CRM pipeline automation, and server deployment. You are essentially building AI employees that do the work of real staff members — generating reports, moving deals through pipelines, sending follow-up emails, updating dashboards, and surfacing insights to managers automatically.
You need to be comfortable figuring things out fast in a rapidly evolving AI tooling landscape.
what we need done.
Pipeline & Lead Hygiene (Sales / BCO)
Auto-flag inactive leads with no activity after 7 days and alert the manager
Auto-flag leads with fewer than 3 contact attempts within 14 days
Enforce the 400-lead cap and remove overflow automatically
Check if a lead is already a client or on the DNC list before it ever gets dialed
Distribute new leads evenly across setters via round-robin logic
Run the weekly BCO city report and flag cities below Alliance minimums
Assign leads as tasks to BCO Scouts in bulk every Monday
HubSpot Logging & Deal Creation (Sales)
Create callback tasks with exact date, time, and context notes
Set appointment booked disposition and trigger the thank-you email automatically
Run the cleaning calculator and populate the deal price field
Associate contact, call, task, and meeting to the deal in a single action
Create the pre-presentation task and assign it to the correct presenter
Enroll prospects in the email sequence when they request email-only follow-up
Flag any HubSpot record not updated before end of shift
Daily Performance Monitoring (Sales / BCO / CS)
Alert the manager if a setter hasn't started dialing by 9:05 AM
Track daily dials and send a pace alert if they are behind by midday
Calculate and report daily talk time per rep
Generate an end-of-day KPI summary per setter automatically
Measure rep downtime — flag any gap over 5 minutes between calls
Ticket Management (Client Services)
Pull the client checklist and verify whether the complaint is in scope before any action is taken
Format the ticket title correctly on every ticket, every time
Determine the correct ticket type (New Concern, R1, Move to BCO) by checking 3-month client history
Create and pin the Master Note with all required fields auto-populated where data exists
Auto-tag Edgar, Peter, Taylor, and the assigned handler on every note
Send the templated client acknowledgment email immediately on ticket creation
Schedule the follow-up email at 8 AM the morning after the correction clean
Send the second follow-up if the client does not respond (Template F)
Auto-open a service ticket when a survey score comes back at 5 or below
Send the R1 Warning Template the moment a second-strike ticket is created
Block ticket closure if the closure checklist is not complete
Flag any ticket open longer than 7 days
Track monthly attrition and alert when it approaches $6K
BCO Pipeline Operations
Move ticket stages automatically as milestones are hit
Calculate profit splits based on building type and billing amount
Check Alliance issue history and active contract count before any match is made
Pin verification notes and tag the right people on every one
Send the Welcome Email on approval and the contract via Google Signature
Download signed contracts and file them to the correct Drive folder automatically
Check inspection report submission by 8 AM after every first clean and alert if missing
Auto-create a BCO ticket the moment an Alliance partner gives up a building
Send email and SMS outreach sequences automatically on no-answer
HR & Hiring
Write the three screening questions for each new job ad
Review Monday.com for new applicants as they auto-populate
Send reference request outreach to candidates via email
Create Google Meet links with correct titles and send confirmation emails
Run the Claude Analyzer after every interview, save the PDF, create the Drive link, and paste it into Monday.com
Log manager interview notes from email into the candidate's Monday.com record
Run the end-of-day board audit and flag any fields that were not updated
Performance Documentation (All Departments)
Pull the full performance history for any employee before a coaching conversation
Check whether a written expectation was ever actually sent
Check whether a deadline was ever actually set
Check Trainual for training completion before any performance action is taken
Draft the post-coaching confirmation email from structured notes
Flag when an escalation threshold is hit (3rd issue, missed deadline pattern)
Compile the full escalation documentation package before a termination
Core Infrastructure (Ongoing)
Deploy and manage OpenClaw AI agents on Linux VPS and Docker — ensure 24/7 uptime
Build, test, and improve agent skills across sales, service, BCO/HR, and executive reporting
Maintain and extend integrations with HubSpot, Monday.com, Google Workspace, and RingCentral
Build and maintain HTML dashboards and reporting tools used by managers daily
Manage the agents' knowledge layer — SOPs, KPIs, org structure, and process documentation
Train non-technical team members on browser-based tools and new systems
Troubleshoot agent failures, API errors, and integration breakdowns — fix them fast
Document everything you build so it is not locked in your head
Required Skills & Experience
Must-Have:
2+ years working with Node.js / JavaScript in a production environment
Experience deploying and managing applications on Linux servers (Ubuntu preferred)
Comfortable with Docker, SSH, and basic DevOps (deploying and maintaining agents on VPS instances)
API integration experience — REST APIs, webhooks, and OAuth flows
Experience with Google Workspace (Drive, Gmail, Calendar, Sheets) including API-level integration
Experience building automated email workflows or CRM automation (HubSpot, Salesforce, or similar)
Strong English communication — you will work directly with non-technical managers who need clear explanations
Ability to train non-technical users on browser-based tools — patience, clear documentation, screen recordings
Self-directed and proactive — you do not wait to be told what is broken, you find it and fix it
Strong Preference:
Experience with AI agent frameworks (OpenClaw, LangChain, CrewAI, AutoGen, or similar)
Prompt engineering skills — writing effective system prompts, managing context windows, and building knowledge bases for LLMs
Experience with HubSpot API (deals, contacts, tickets, pipelines, workflows) and Monday.com API
Experience building agents or bots that automate multi-step business processes (not just chatbots)
Familiarity with vector databases (ChromaDB, Pinecone) and RAG architectures
HTML/CSS for building dashboards and reports
Experience working with a small team remotely across time zones
Nice-to-Have:
Python scripting (some of our automation uses Python)
Experience with Pipedream or serverless deployment
Familiarity with Anthropic's Claude API or OpenAI API
Background in business process automation (not just coding — understanding why we automate)
Experience with Make.com, Zapier, or n8n workflow platforms
How to Apply
Do NOT send a generic cover letter. We will ignore it.
Step 1: Fill out the application form here: wkf.ms/3PhxiwP — attach your resume/CV.
Step 2: Record a 5–8 minute video answering the four questions below. Upload it to Google Drive, Loom, or YouTube (unlisted) and paste the link in the form.
VIDEO QUESTIONS (all four are required):
Show us your screen and walk through a project where you built or deployed an AI agent or automated workflow. What did it do, what tools did you use, and what broke along the way? We want to see a real project, not a slide deck.
Our managers are not developers. Explain what an API is and why it matters — as if you are talking to someone who has never written a line of code. This tests whether you can communicate with our team.
You are tasked with building an AI agent that automatically sends a follow-up email to a client 3 days after a deal moves to "Closed Won" in a CRM. Walk us through how you would build that — what tools, what steps, what could go wrong, and how you would monitor it.
What AI tools or frameworks have you used in the last 90 days? Show us something you are currently working on or learning. We want to see that you are active in this space right now, not that you took a course two years ago.
Applications with completed videos get reviewed first. Bonus points if you also include a GitHub, portfolio, or demo link.
Compensation & Growth
$1,200 – $3,400 CAD/month depending on experience and skill match
Performance reviews at 30, 60, and 90 days with potential raise based on results
Long-term role — we are building a permanent AI operations layer, not a one-off project
Autonomy — you own the technical stack. If something should be done differently, you tell us
Growth opportunity — as One Janitorial scales, so does the AI infrastructure and your role with it
You will be the technical owner of our AI agent ecosystem. We currently run 30+ automated skills and agents through Claude (Anthropic), OpenClaw, and various API integrations (HubSpot, Monday.com, Google Workspace, RingCentral). Your job is to deploy, maintain, improve, and scale these agents — and build new ones as the business needs them.
This is NOT a traditional software engineering role. You will be working with AI agent frameworks, prompt engineering, API integrations, automated email systems, CRM pipeline automation, and server deployment. You are essentially building AI employees that do the work of real staff members — generating reports, moving deals through pipelines, sending follow-up emails, updating dashboards, and surfacing insights to managers automatically.
You need to be comfortable figuring things out fast in a rapidly evolving AI tooling landscape.
what we need done.
Pipeline & Lead Hygiene (Sales / BCO)
Auto-flag inactive leads with no activity after 7 days and alert the manager
Auto-flag leads with fewer than 3 contact attempts within 14 days
Enforce the 400-lead cap and remove overflow automatically
Check if a lead is already a client or on the DNC list before it ever gets dialed
Distribute new leads evenly across setters via round-robin logic
Run the weekly BCO city report and flag cities below Alliance minimums
Assign leads as tasks to BCO Scouts in bulk every Monday
HubSpot Logging & Deal Creation (Sales)
Create callback tasks with exact date, time, and context notes
Set appointment booked disposition and trigger the thank-you email automatically
Run the cleaning calculator and populate the deal price field
Associate contact, call, task, and meeting to the deal in a single action
Create the pre-presentation task and assign it to the correct presenter
Enroll prospects in the email sequence when they request email-only follow-up
Flag any HubSpot record not updated before end of shift
Daily Performance Monitoring (Sales / BCO / CS)
Alert the manager if a setter hasn't started dialing by 9:05 AM
Track daily dials and send a pace alert if they are behind by midday
Calculate and report daily talk time per rep
Generate an end-of-day KPI summary per setter automatically
Measure rep downtime — flag any gap over 5 minutes between calls
Ticket Management (Client Services)
Pull the client checklist and verify whether the complaint is in scope before any action is taken
Format the ticket title correctly on every ticket, every time
Determine the correct ticket type (New Concern, R1, Move to BCO) by checking 3-month client history
Create and pin the Master Note with all required fields auto-populated where data exists
Auto-tag Edgar, Peter, Taylor, and the assigned handler on every note
Send the templated client acknowledgment email immediately on ticket creation
Schedule the follow-up email at 8 AM the morning after the correction clean
Send the second follow-up if the client does not respond (Template F)
Auto-open a service ticket when a survey score comes back at 5 or below
Send the R1 Warning Template the moment a second-strike ticket is created
Block ticket closure if the closure checklist is not complete
Flag any ticket open longer than 7 days
Track monthly attrition and alert when it approaches $6K
BCO Pipeline Operations
Move ticket stages automatically as milestones are hit
Calculate profit splits based on building type and billing amount
Check Alliance issue history and active contract count before any match is made
Pin verification notes and tag the right people on every one
Send the Welcome Email on approval and the contract via Google Signature
Download signed contracts and file them to the correct Drive folder automatically
Check inspection report submission by 8 AM after every first clean and alert if missing
Auto-create a BCO ticket the moment an Alliance partner gives up a building
Send email and SMS outreach sequences automatically on no-answer
HR & Hiring
Write the three screening questions for each new job ad
Review Monday.com for new applicants as they auto-populate
Send reference request outreach to candidates via email
Create Google Meet links with correct titles and send confirmation emails
Run the Claude Analyzer after every interview, save the PDF, create the Drive link, and paste it into Monday.com
Log manager interview notes from email into the candidate's Monday.com record
Run the end-of-day board audit and flag any fields that were not updated
Performance Documentation (All Departments)
Pull the full performance history for any employee before a coaching conversation
Check whether a written expectation was ever actually sent
Check whether a deadline was ever actually set
Check Trainual for training completion before any performance action is taken
Draft the post-coaching confirmation email from structured notes
Flag when an escalation threshold is hit (3rd issue, missed deadline pattern)
Compile the full escalation documentation package before a termination
Core Infrastructure (Ongoing)
Deploy and manage OpenClaw AI agents on Linux VPS and Docker — ensure 24/7 uptime
Build, test, and improve agent skills across sales, service, BCO/HR, and executive reporting
Maintain and extend integrations with HubSpot, Monday.com, Google Workspace, and RingCentral
Build and maintain HTML dashboards and reporting tools used by managers daily
Manage the agents' knowledge layer — SOPs, KPIs, org structure, and process documentation
Train non-technical team members on browser-based tools and new systems
Troubleshoot agent failures, API errors, and integration breakdowns — fix them fast
Document everything you build so it is not locked in your head
Required Skills & Experience
Must-Have:
2+ years working with Node.js / JavaScript in a production environment
Experience deploying and managing applications on Linux servers (Ubuntu preferred)
Comfortable with Docker, SSH, and basic DevOps (deploying and maintaining agents on VPS instances)
API integration experience — REST APIs, webhooks, and OAuth flows
Experience with Google Workspace (Drive, Gmail, Calendar, Sheets) including API-level integration
Experience building automated email workflows or CRM automation (HubSpot, Salesforce, or similar)
Strong English communication — you will work directly with non-technical managers who need clear explanations
Ability to train non-technical users on browser-based tools — patience, clear documentation, screen recordings
Self-directed and proactive — you do not wait to be told what is broken, you find it and fix it
Strong Preference:
Experience with AI agent frameworks (OpenClaw, LangChain, CrewAI, AutoGen, or similar)
Prompt engineering skills — writing effective system prompts, managing context windows, and building knowledge bases for LLMs
Experience with HubSpot API (deals, contacts, tickets, pipelines, workflows) and Monday.com API
Experience building agents or bots that automate multi-step business processes (not just chatbots)
Familiarity with vector databases (ChromaDB, Pinecone) and RAG architectures
HTML/CSS for building dashboards and reports
Experience working with a small team remotely across time zones
Nice-to-Have:
Python scripting (some of our automation uses Python)
Experience with Pipedream or serverless deployment
Familiarity with Anthropic's Claude API or OpenAI API
Background in business process automation (not just coding — understanding why we automate)
Experience with Make.com, Zapier, or n8n workflow platforms
How to Apply
Do NOT send a generic cover letter. We will ignore it.
Step 1: Fill out the application form here: wkf.ms/3PhxiwP — attach your resume/CV.
Step 2: Record a 5–8 minute video answering the four questions below. Upload it to Google Drive, Loom, or YouTube (unlisted) and paste the link in the form.
VIDEO QUESTIONS (all four are required):
Show us your screen and walk through a project where you built or deployed an AI agent or automated workflow. What did it do, what tools did you use, and what broke along the way? We want to see a real project, not a slide deck.
Our managers are not developers. Explain what an API is and why it matters — as if you are talking to someone who has never written a line of code. This tests whether you can communicate with our team.
You are tasked with building an AI agent that automatically sends a follow-up email to a client 3 days after a deal moves to "Closed Won" in a CRM. Walk us through how you would build that — what tools, what steps, what could go wrong, and how you would monitor it.
What AI tools or frameworks have you used in the last 90 days? Show us something you are currently working on or learning. We want to see that you are active in this space right now, not that you took a course two years ago.
Applications with completed videos get reviewed first. Bonus points if you also include a GitHub, portfolio, or demo link.
Compensation & Growth
$1,200 – $3,400 CAD/month depending on experience and skill match
Performance reviews at 30, 60, and 90 days with potential raise based on results
Long-term role — we are building a permanent AI operations layer, not a one-off project
Autonomy — you own the technical stack. If something should be done differently, you tell us
Growth opportunity — as One Janitorial scales, so does the AI infrastructure and your role with it