Lead Instructor - AI Solutions Engineering Program

Edversity is seeking a part-time Lead Instructor to oversee its Forward Deployed AI Engineer program, a fully remote, 12-week live online course. This role is ideal for experienced AI professionals who want to teach alongside their current work. Forward Deployed AI Engineers collaborate directly with clients to identify business challenges and develop AI solutions, including large language model (LLM) applications, agents, and automation, deployed in real-world environments. As Lead Instructor, you will be responsible for guiding the academic delivery and technical direction of the program, working closely with teaching assistants, and preparing students for client-facing AI engineering roles.

Key Responsibilities

Program Leadership:
- Develop and maintain the curriculum, including course structure, learning outcomes, projects, and assessments.
- Support and mentor teaching assistants to ensure consistent teaching quality.
- Establish grading criteria and project evaluation rubrics.
- Collaborate with Edversity’s team to align the program with industry hiring trends and employer needs.
- Provide regular updates on student progress and recommend program improvements.

Teaching & Mentorship:
- Deliver live online lectures, labs, and workshops covering core and advanced AI engineering topics.
- Teach practical skills such as LLM application development, prompt engineering, retrieval-augmented generation (RAG), AI agents, tool usage, fine-tuning basics, and model evaluation.
- Lead client-simulation exercises focused on requirement gathering, solution scoping, prototyping, and stakeholder presentations.
- Supervise capstone projects where students build and deploy production-ready AI solutions.
- Review student code and architecture, offering structured, actionable feedback.
- Coach students on consulting, communication, and documentation skills essential for client-facing roles.

Continuous Improvement:
- Keep course content up to date with the latest AI models, frameworks, and deployment practices.
- Contribute reusable teaching materials, lab environments, starter templates, and project datasets.

Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, AI, Data Science, or a related field.
- Minimum of 3 years of industry experience in AI/ML engineering, software engineering, solutions engineering, or forward deployed engineering, including hands-on experience shipping AI or LLM-based products.
- At least 1 year of teaching, corporate training, or team leadership experience.
- Strong proficiency in Python and working knowledge of JavaScript/TypeScript.
- Proven experience deploying AI applications to cloud environments and integrating them with client systems.
- Excellent communication and presentation skills in English and Urdu.
- Availability to teach live online sessions on scheduled days with a reliable internet connection and appropriate remote teaching setup.

Preferred Qualifications and Benefits
- Prior experience in forward deployed, solutions engineering, or AI consulting roles involving direct client interaction.
- Cloud or AI certifications such as AWS, Azure, or Google Cloud Platform.
- Knowledge of AI safety, data privacy, security, and responsible AI practices in client deployments.
- Experience designing bootcamp-style or project-based technical programs.

Tools & Technologies
The role involves working with a broad set of tools and technologies including Python, JavaScript/TypeScript, FastAPI, Flask, Node.js, React, Streamlit, Gradio, and SQL. Familiarity with LLM providers like OpenAI, Anthropic, Google Gemini, and open-source models via Hugging Face is essential. AI engineering frameworks such as LangChain and LangGraph, vector databases like Pinecone and Weaviate, and evaluation tools including LangSmith and Weights & Biases are commonly used. Cloud platforms (AWS, Azure, Google Cloud), containerization (Docker, Kubernetes), CI/CD pipelines, API integrations, and collaboration tools like Git, Jira, and Zoom are integral to the role. Teaching tools include Google Classroom or LMS platforms, virtual whiteboarding apps, and session recording software.

This position offers the opportunity to shape the next generation of AI engineers while maintaining flexibility through part-time, fully remote work.