Sales Engineer Solutions Consultant

Job Description:

Position: Course Instructor (AI Solutions Architect / AI Expert)

Location: Remote / Flexible

Duration: Contract-based (with potential for future opportunities)

Salary: Rev Share

About the Role:

We are seeking an experienced AI Solutions Architect or AI Expert to deliver a comprehensive course on AI Agents and Multi-Agent Systems (MAS). This is an exciting opportunity to teach and inspire the next generation of AI professionals, guiding them through foundational concepts, practical applications, and real-world problem-solving with AI agents.

As an AI Solutions Architect / AI Expert, you will be responsible for delivering lectures, facilitating discussions, providing mentorship, and supervising hands-on projects. You will work closely with guest speakers, technical instructors, and ethics experts to create a well-rounded learning experience for the students.

Key Responsibilities:

• Deliver lectures and workshops on AI agents, multi-agent systems, and their real-world applications.


• Develop and maintain course content, including slides, assignments, and hands-on projects.


• Guide students through the design and implementation of AI agents and MAS.


• Provide feedback and support to students on their projects and assignments.


• Collaborate with other instructors and guest speakers to ensure a cohesive learning experience.


• Stay up-to-date with current trends and advancements in AI and multi-agent systems.


• Assess student performance through projects, exams, and other assessments.

Required Qualifications:

• Advanced degree (Master’s or PhD) in AI, Computer Science, or a related field.


• Proven industry experience (5+ years) in AI solutions architecture, machine learning, or multi-agent systems development.


• Strong understanding of AI agent types, multi-agent systems, and their applications in real-world settings.


• Experience with AI frameworks (e.g., TensorFlow, PyTorch, OpenAI Gym, ROS) and agent-based modeling.


• Familiarity with programming languages used in AI (Python, Java, etc.).


• Excellent communication skills and the ability to explain complex concepts to a wide range of learners.


• Prior teaching or mentoring experience is a plus.

Preferred Skills:

• Experience with autonomous systems, robotics, or swarm intelligence.


• Knowledge of AI ethics, privacy regulations, and regulatory frameworks.


• Expertise in project-based learning and the ability to guide students through practical applications.


• Passion for educating and inspiring future AI leaders.

Course Outline:

1. Module 1: Introduction to AI Agents
   
   
   
   • What are AI Agents?
   
   
   • The Role of AI Agents in Modern Technology
   
   
   • How AI Agents Work
   
   
   • Basic AI Agent Architecture
   
   
   
   


2. Module 2: Exploring Types of AI Agents
   
   
   
   • Simple Reflex Agents
   
   
   • Model-Based Reflex Agents
   
   
   • Goal-Based Agents
   
   
   • Utility-Based Agents
   
   
   • Learning Agents
   
   
   
   


3. Module 3: Introduction to Multi-Agent Systems (MAS)
   
   
   
   • What are Multi-Agent Systems?
   
   
   • MAD Frameworks and Architectures
   
   
   • Challenges in MAS
   
   
   
   


4. Module 4: Applications of AI Agents and MAS
   
   
   
   • AI Agents in Industry
   
   
   • MAS in Complex Problem-Solving
   
   
   • AI Agents and MAS in Financial Services
   
   
   
   


5. Module 5: Designing AI Agents and Multi-Agent Systems
   
   
   
   • Designing a Single AI Agent
   
   
   • Designing and Managing Multi-Agent Systems
   
   
   • Tools and Frameworks for Agent Development
   
   
   
   


6. Module 6: Ethical Considerations and Future of AI Agents
   
   
   
   • Ethical Implications of AI Agents
   
   
   • The Future of AI Agents and MAS
   
   
   • Legal and Regulatory Issues
   
   
   
   


7. Module 7: Hands-On Project
   
   
   
   • Project Guidelines
   
   
   • Project Review and Discussion
   
   
   
   

Why Join Us?

• Impact: Shape the future of AI by teaching and mentoring the next generation of AI professionals.


• Flexibility: Work remotely with flexible hours.


• Collaborative Environment: Collaborate with experts in AI, industry leaders, and ethical advisors.


• Professional Development: Opportunities for further involvement in future courses and projects.