Experienced B2b Sales & Appointment Setter for Ai Tech Company (Remote)

We are a Hong Kong-based technology company specializing in cutting-edge ai engine solutions and ai-powered consumer services. We are building a high-performance, fully remote global team to accelerate our international business growth.

Job Type: Full Time

Wage / Salary: 1,500 USD + performance incentive

Hours: Monday–Friday (flexible, aligned to HK/global client time zones)

Location: 100% Remote (Open to global applicants)

Key Responsibilities
Conduct outbound prospecting via email, LinkedIn, and video calls to international B2B clients.  

Qualify leads and schedule high-value discovery calls / demos for senior stakeholders.  

Manage the full sales cycle from first contact through to close.  

Maintain accurate pipeline records in CRM (HubSpot or equivalent).  

Track and analyze your own performance data weekly (outreach volume, reply rate, conversion rate, win rate) to optimize the funnel.  

Identify funnel bottlenecks using data, form clear hypotheses, and run experiments to improve them.

Research target accounts, market trends, and competitor activity.

⚠️ Our Core Philosophy: Quantitative Before Qualitative
At our company, every business problem is first analyzed with numbers.

❌ "I feel the campaign isn't working well." — NOT analysis.

⭕ "Reply rate dropped from 4.2% to 1.8% week-over-week, likely caused by the subject line change on Tuesday." — this is analysis.  

If you cannot define problems with data, you cannot solve them. We need someone who naturally reaches for numbers and has done this in previous roles.  

Requirements
Must Have:
Full Professional Proficiency in English: Fluent in both written and spoken English for all business operations (assessed during the interview).

Education: Graduate of a recognized university (MUST include your university and degree).

Data-Driven Experience: Hands-on experience analyzing sales/marketing performance using quantitative metrics (KPIs, funnel metrics, conversion rates).

Independence: Proven ability to work independently with strong proactive reporting habits.

Nice to Have:
Experience in BPO, multinational corporations, or tech/SaaS/AI industries.

Outbound sales track record (cold email / LinkedIn outreach) with measurable results.

CRM experience (HubSpot, Salesforce, etc.), Including building reports or dashboards.

Do NOT Apply If:
You analyze problems primarily through "feelings" or "general impressions".

You have never personally tracked your own KPIs or require constant supervision.

You cannot provide proof of your university degree or lack spoken English fluency.

How to Apply
Applications that do not follow these instructions will not be reviewed.
Please send your application to the designated email with the subject line exactly as written:
"AI Sales – [Your Full Name] – [Your University]"  

Your application MUST include all of the following:  

Your resume / cv (pdf format)  

a 2–3 minute loom video introduction link (see instructions below)  

answers to all four screening questions below (in the body of your email)  

📹 loom video instructions
record a short 2–3 minute video at loom.com where you:  

Introduce yourself in English (name, university, degree, current responsibilities, years of experience).  

Describe one specific situation where you used data or numbers to identify a problem at work — what were the numbers, what did you conclude, and what did you do? (vague answers will be rejected).  

Tell us: What does "working independently" mean to you in practice?  

📝 Screening Questions (Answer all 4 in English)
 
Q1: Which university did you graduate from, and what was your degree?  

Q2: Describe a time you had to reach a decision or solve a problem at work without clear instructions from your manager. What did you do, and what was the result?  

Q3: Have you used a CRM tool before? If yes, which one, and how did you use it specifically? Please include numbers (e.g., Pipeline value, conversion rates, deals closed).  

Q4: (Quantitative Analysis Case — answer with numbers)
Imagine you sent 500 cold emails last month and received the following results:  

Open rate: 38% (industry average: 40%)  

Reply rate: 1.2% (industry average: 3%)  

Booked appointments: 2 | Closed deals: 0  

Based on these numbers alone:
(a) Where is the biggest bottleneck in the funnel, and why? Cite specific numbers.
(b) What two specific experiments would you run next month to improve this, and what result would tell you whether each experiment worked?