Product Deep Dive 1: Help People Find Jobs

Day 1: Email from the recruiter

Prompt

As an employee at an all-remote company, you will primarily communicate in writing. As a result, we’ve created a component to our interview process to ensure we’re selecting people who not only excite us in standard interview formats, but have proven their effectiveness in written and asynchronous communication.

Create two write-ups (one Vision, one Iteration) on the problem statement “Helping people find a job.”

For the Vision part of the process, we want to unpack the problem space to discover who is facing the problem; what related, underlying root problems may contribute; and a vision for how we could solve the problem.

Once we have the vision, we want to Iterate. What is the smallest possible thing you could ship in this area in 1-2 weeks? How would you define the first iteration for this feature?

Day 4: Assignment submission

Solution

Vision

Fractional AI talent initiative to capture a share of the $ 91B AI consulting market.

Assumptions

• Role & Context: Assume Iʼm a PM at a global HR platform designed to simplify hiring, tasked with solving the problem statement: “helping people find a job” within its existing global HR solution.
• Geographic Focus: Start with the U.S. market, scaling globally post-launch.
• Platform Constraints: Leverage the company’s existing hiring management and compliance tools to minimize development friction.

Product Motivation

In todayʼs rapidly evolving business landscape, artificial intelligence (AI) is transforming industries at an unprecedented pace. However, businesses face a critical challenge: finding and accessing top-tier AI talent to drive innovation. At the same time, many highly skilled AI professionals seek flexible, fractional employment opportunities but lack a platform to showcase their expertise and connect with global employers.

This is where our company can lead the charge by introducing , a platform designed to bridge the gap between businesses and sought-after AI experts. It empowers businesses to innovate cost-effectively while enabling experts to monetize niche skills globally. This initiative aligns seamlessly with Remoteʼs mission of creating opportunities everywhere while unlocking a high-growth market segment that complements the existing product suite.

The Opportunity

• Market Demand: The global AI market is projected to grow to $3.68 T by 2034, with businesses across industries seeking specialized AI expertise to remain competitive. However, 75 % of employers report difficulty in finding skilled AI professionals.
• Talent Supply: A growing number of individuals are mastering AI tools and applications but lack platforms to showcase their skills or secure fractional employment opportunities.
• Fractional Hiring Trend: 75 % of employers struggle to find AI talent, while fractional hiring reduces costs by 30-40%.

Strategic Context

• Market Trend: 75% of employers struggle to find AI talent, while fractional hiring reduces costs by 30-40%.
• Competitive Edge: However, 75% of employers report difficulty in finding skilled AI professionals.
• Mission Statement: “To democratize access to AI expertise by creating a trusted global marketplace where businesses and professionals thrive through flexible, impactful collaboration.”

Vision Draft

Who is experiencing this problem?

Two primary groups (demand & supply) are experiencing significant challenges in the fractional AI talent space:

1. AI Professionals: Individuals who have mastered AI tools and practical business applications but lack platforms to showcase their expertise and find fractional employment opportunities globally.
2. Businesses (primarily SMBs): Organizations that need specialized AI expertise but cannot justify full-time hires due to budget constraints or periodic project needs.
3. HR and Talent Acquisition Teams: Professionals struggling to find compliant ways to source specialized AI talent across borders.

Is there a particular persona that you would like to focus on?

Mid-career AI Consultants represent our primary target persona:

• Professionals with 5-10 years of experience who have left corporate roles to pursue independent consulting.
• Specialists in high-demand fields like machine learning engineering, LLM development, AI tools or AI implementation strategy.

Example: Priya, 34, an NLP specialist who left a FAANG company to consult. Despite her expertise, she struggles to find businesses willing to hire fractionally and faces administrative hurdles when working across borders.

Why did I pick this segment?

• High demand for their niche skills (e.g., LLM optimization)
• Underserved by generic platforms.

What do they value?

Our target persona values:

• Professional Recognition: Validation of their expertise and specialized skills
• Flexibility: Control over their schedule and project selection
• Global Opportunity Access: Ability to work with diverse clients regardless of location
• Simplified Administration: Streamlined contracts, payments, and compliance
• Financial Security: Consistent pipeline of opportunities to ensure stable income
• Meaningful Work: Projects that leverage their expertise and create genuine impact

What are their pain points?

Key pain points include:

1. Discovery Challenges: No centralized platform for finding fractional AI roles
2. Credibility Gap: Difficulty proving expertise without formal channels
3. Administrative Burden: Managing cross-border compliance, contracts, and taxes
4. Income Volatility: Unpredictable project flow creating financial uncertainty
5. Project Mismatch: Being hired for projects that donʼt align with their specialized skills
6. Global Payment Complexities: Navigating different payment systems and currencies

If we had a magic wand and could accomplish anything, how would we solve this problem?

With unlimited resources, we would create:

• A platform that automatically matches AI experts with perfect-fit projects using advanced algorithms.
• A global compliance engine that handles all tax, legal, and payment considerations transparently.
• A verification system that instantly validates specialized AI skills and expertise.
• A pipeline management tool ensuring consistent, high-quality opportunities.
• A reputation ecosystem that builds credibility through peer reviews and outcome metrics.
• A global community connecting AI experts for collaboration and knowledge-sharing.

What is the vision for this product or service at maturity?

At maturity, Fractional AI Talent platform would be:

• The definitive global marketplace for AI expertise, trusted by both professionals and businesses.
• A comprehensive ecosystem that standardizes fractional hiring across the AI industry.
• An integrated solution within Remoteʼs infrastructure that seamlessly manages compliance, payments, and contracts.
• A platform that enables businesses of all sizes to innovate with AI without traditional hiring constraints.
• A career accelerator for AI professionals seeking independence and global impact.

What would make this product, feature, or service loved by its users?

Users would love this product for:

• Frictionless Experience: Simplified discovery, hiring, and management processes.
• High-Quality Matches: Connections that lead to successful outcomes and lasting relationships.
• Transparent Pricing: Clear fee structures that maximize earnings for professionals.
• Community Access: Opportunities to connect with peers and industry leaders.
• Administrative Relief: Automation of contracts, payments, and compliance.
• Professional Growth: Access to cutting-edge projects and skill development opportunities.

How would we measure success? What would things look like if we achieved this vision?

Success metrics would include:

When achieved, Remote would be recognized as the global leader in fractional AI talent, driving innovation across industries while creating meaningful opportunities for professionals worldwide.

P.S.: The numbers are gathered through a mix of desk research and logical reasoning, making certain assumptions. In a real-life project, Remote can enhance confidence in its success metrics by utilising a structured, data-driven approach that validates assumptions against historical performance, industry benchmarks, and continuous measurement.

Outcome Alignment

This initiative aligns with Remoteʼs mission to simplify global hiring while tapping into a $ 91 B AI consulting market. By focusing on credibility and discovery, the platform could increase customer acquisition among SMBs and drive engagement through premium features (e.g., advanced analytics for HR teams).

Final Statement

Launching a fractional AI talent platform with skill verification and matchmaking will position the company as the leader in flexible AI hiring, driving a 15-20% increase in enterprise customer acquisition and capturing a share of the $ 91B AI consulting market by 2035.

Iteration

Pain Point Prioritization

1. Discovery Challenges: No centralized platform for finding fractional AI roles
2. Credibility Gap: Difficulty proving expertise without formal channels

Prioritization Rationale

• Severity: Prevents experts from finding relevant opportunities.
• Frequency: Persistent across all job searches.

MVP Engineering Brief

Assumption: The product discovery phase is complete, including problem definition, prototyping and testing.

What could we do this week?

Scope: We’ll create a minimal “AI Talent Showcase” feature within Remote’s existing contractor management platform. This MVP focuses on testing the core hypothesis: that AI professionals want a dedicated space to showcase their expertise and that businesses are interested in finding them.

Phase 1 Features:

1. Expert Profile Extension:
   1. Add an “AI Expertise” section to existing contractor profiles
   2. Include 5-10 predefined AI skill tags (NLP, Prompt Engineering, Tool Expertise, etc.)
   3. Allow uploading of 1-2 case studies/portfolio items
2. Simple Discovery Page:
   • A basic searchable directory of AI professionals
   • Filtering by key skills and availability
   • Integration with existing Remote contractor features
3. Connection Tracking:
   • Simple analytics to track profile views and connection requests
   • Manual matching support by our team for initial users

How big of a team do you need? Who do you want on it?

• 2 Full-stack engineers (focus on profile extensions and search functionality)
• 1 Front-end engineer (for the discovery interface)
• 1 Designer (part-time, for designing UI components)
• 1 Data analyst (part-time, for tracking engagement metrics)

What hypothesis do we need to test first?

Risks Mitigation:

What could we do in one month?

Phase 2 Features:

1. Enhanced Profile Verification:
   • Integration with certification providers (AWS, Google, etc.)
   • LinkedIn skill endorsement import
2. Basic Matching Algorithm:
   • Simple recommendation engine based on skills and requirements
   • Email notifications for new matches
3. Availability Management:
   • Calendar integration to show fractional availability
   • Booking request functionality
4. Deeper Platform Integration:
   • Connect to Remote’s payment and compliance systems
   • Initial contract templates for fractional AI work

What could we do in three months?

Phase 3 Features:

1. AI Skill Verification System:
   • Peer review process for skill validation
   • Standardized skill badges with verification levels
2. Advanced Matching Algorithm:
   • Project-specific matching based on detailed requirements
   • Success prediction based on historical data
3. Project Management Tools:
   • Milestone tracking for fractional engagements
   • Project outcome documentation
4. Community Features:
   • Discussion forums for AI professionals
   • Knowledge sharing and mentorship opportunities

What is the hardest part of this problem to solve?

1. Effective Skill Verification:
   • Challenge: Objectively verifying specialized AI skills is difficult without standardized assessments
   • Approach: Start with self-reporting and third-party certification validation; develop more sophisticated verification in phases
2. Quality Matching at Scale:
   • Challenge: Maintaining high-quality matches as the platform grows
   • Approach: Begin with a manual review of matches while collecting data to train algorithms
3. Differentiation from Generic Platforms:
   • Challenge: Ensuring our solution provides unique value beyond existing freelance platforms
   • Approach: Focus on Remote’s strengths in compliance and global payments as key differentiators

Day 6: Questions (by adding comments on the doc) by the reviewer

Day 7: Response to questions

Day 7: More questions by the reviewwer

Day 8: Response to open questions and closure