The main objective of this project is to identify and attract Canadian talent in AI software engineering, fulfilling the company’s need for highly skilled professionals in this specialized field. The learner will conduct extensive market research and implement effective recruitment strategies to source at least 10 qualified AI software engineering candidates. This involves understanding the nuances of AI technology, the software engineering market, and effective recruitment tactics. The goal is to enhance the company's Canadian talent pool with individuals capable of advancing our AI innovations and projects.

Outcomes Involved:

1. Qualified Candidate Pool: A curated list of at least 10 highly qualified Canadian AI software engineering candidates ready for further interview and assessment processes.

2. Effective Recruitment Strategy: A comprehensive and tailored recruitment strategy specifically developed for sourcing AI software engineering talent.

3. Market Insights Report: A detailed report highlighting current trends, demands, and skillsets within the AI software engineering job market.

4. Enhanced Company Profile: A strengthened employer brand in the AI and tech community, attracting higher caliber candidates.

5. Streamlined Recruitment Process: An established and efficient recruitment process specifically designed for AI software engineering roles, including pre-screening and interview coordination.

6. Candidate Engagement Metrics: Data and metrics regarding candidate engagement and response rates to different recruitment strategies and channels.

7. Feedback Analysis System: A system for collecting and analyzing feedback from both the hiring team and candidates to refine ongoing recruitment practices

Tasks List:

· Market Research: Conduct in-depth research on the current AI software engineering job market, identifying key skills and qualifications in demand.

· Talent Identification: Utilize various sourcing methods to identify potential candidates who meet the specific requirements for AI software engineering roles.

· Recruitment Strategy Development: Create and implement effective recruitment strategies tailored to the AI software engineering sector.

· Communication Plan: Develop a plan to engage with potential candidates through various channels, ensuring clear and compelling communication of opportunities. Maintain communication with potential candidates, including initial outreach, follow-ups, and keeping them engaged throughout the recruitment process.

· Candidate Screening: Pre-screen potential candidates to assess their fit for the role based on their skills, experience, and alignment with company values.

· Interview Coordination: Organize and schedule interviews between shortlisted candidates and the hiring team.

· Feedback Collection and Analysis: Gather feedback from the hiring team post-interviews to refine the recruitment process.

· Documentation and Reporting: Maintain detailed records of the recruitment process and provide regular updates on the progress.

· Employer Branding: Contribute to employer branding initiatives that make the company attractive to top AI talent.

Support & Mentorship:

1. Regular Guidance: Weekly meetings with the learner to discuss progress, provide feedback, and offer guidance from our HR and AI department leads.

2. Resource Provision: Access to industry reports, talent databases, and recruitment tools.

3. Training Sessions: Initial training sessions on our company’s AI projects, culture, and the specific skills required for AI software engineering roles.

4. Communication Channels: Providing access to company communication platforms for reaching out to potential candidates.

5.  Feedback Mechanisms: Constructive feedback on the recruitment strategies and communication approach with candidates.

Ideal Learners:

· Human Resources Students: Individuals pursuing studies in human resources, particularly those interested in recruitment and talent acquisition in the tech industry.

· Business and Management Students: Students specializing in business or management focusing on human resource management, interested in applying their knowledge to the technology sector.

· Marketing and Communications Students: Those studying marketing or communications, looking to apply their skills in employer branding and candidate engagement within a tech context.

· Data Analysis Enthusiasts: Individuals with a keen interest in data analysis, aiming to apply these skills in a recruitment and HR context, especially in tech talent acquisition.

· Emerging HR Tech Professionals: Aspiring HR professionals looking to specialize in technology-driven recruitment strategies and processes.

Benefits to Learners:

1. Industry-Specific Recruitment Skills: Gain hands-on experience in recruiting for highly specialized roles in the AI and tech industry.

2. Understanding of AI Job Market: Develop a deep understanding of the AI software engineering job market, including in-demand skills and qualifications.

3. Networking Opportunities: Connect with professionals in both the HR and AI/tech sectors, expanding professional networks and gaining industry insights.

4. Practical Application of HR Theories: Apply academic theories and concepts in human resources to practical, real-world tech recruitment scenarios.

5. Enhanced Communication Skills: Improve verbal and written communication skills, crucial for engaging effectively with candidates and stakeholders.