Agentic AI Engineer Instructor (Contract) at WeCloudData in Remote

About Us

WeCloudData is a leading data and AI training academy dedicated to delivering high-quality education to students, professionals, and corporate clients. We also provide consulting and career services to support learners and organizations beyond the classroom.

Over the next decade, our goal is to impact millions of learners and help shape the future of work through excellent learning experiences, technological innovation, and work-integrated learning opportunities. We are committed to staying at the forefront of technology and workforce education.

Job Description

We are looking for experienced and motivated AI Engineering Instructors to support our 6-week Overseas Bootcamp, scheduled to begin around Nov 2026. We are hiring both Onsite and Online Instructors for delivery in Saudi Arabia.

This role is ideal for candidates with strong hands-on experience in AI engineering, machine learning, deep learning, generative AI, agentic systems, and production deployment, combined with strong communication and mentoring skills. The curriculum covers the AI lifecycle, from data preparation and model development to building, evaluating, and operating LLM applications and AI agents.

Candidates must be available to commit to the full program period, with additional availability potentially required for onboarding, preparation, and program setup.

Key Responsibilities

• Deliver lectures, demonstrations, hands-on labs, technical review sessions, and Q&A sessions throughout the bootcamp.
• Teach Python fundamentals and Generative AI basics for pre-work alignment, followed by Python programming and ML fundamentals for baseline alignment.
• Guide students through deep learning fundamentals, architectures, model training, and inference pipelines, as well as Large Language Model (LLM) fundamentals, prompting, evaluation, and safety.
• Guide students in building Retrieval-Augmented Generation (RAG) pipelines with embeddings and vector databases, single-agent systems with reasoning loops and tool use, and multi-agent systems with memory, planning, and coordination.
• Guide students in building end-to-end AI applications using LLMs, prompt engineering, RAG, AI agents, workflow orchestration, and APIs.
• Teach model deployment patterns and MLOps foundations, including CI/CD, monitoring, drift detection, and retraining strategies. Guide learners in deploying, monitoring, and operating AI systems, including production-ready agentic architectures.
• Teach agentic platforms, including LangGraph and AutoGen concepts, and agent reliability, safety, guardrails, and AgentOps. Cover LLMOps and AgentOps practices for evaluation, monitoring, observability, cost control, latency control, and performance optimization.

General Required Qualifications

• Minimum of 3 years of relevant professional experience in AI engineering, machine learning, deep learning, generative AI, software engineering, full-stack development, enterprise AI architecture, cloud computing, or a closely related technical field.
• Practical experience with LLMs, prompting, RAG, and agent workflows, including tool-calling agents, reasoning loops, multi-agent architectures, memory, planning, coordination, structured outputs, and human-in-the-loop controls.
• Understanding of end-to-end AI system design, model deployment and MLOps, and AgentOps and LLMOps concepts, including evaluation, monitoring, reliability, cost control, and latency control.
• Good understanding of applied machine learning, generative AI, and LLMs, including selecting appropriate approaches such as prompting, RAG, fine-tuning, AI agents, or traditional ML.
• Familiarity with model serving, inference endpoints, APIs, containerized applications, cloud deployment, CI/CD, drift detection, and retraining strategies.
• Practical experience testing and debugging ML models, deep learning pipelines, LLM applications, RAG systems, and AI agents.
• Strong understanding of AI safety and security, including prompt injection, data privacy, access control, guardrails, and responsible AI practices.
• Strong English communication skills, both spoken and written, with the ability to explain technical concepts clearly.
• Ability to work effectively with students, instructors, teaching assistants, and program staff.
• Ability to quickly adapt to new tools, platforms, technical environments, and existing teaching materials.

Location

- Onsite Instructor: In-person delivery in Saudi Arabia, with approved travel-related expenses covered.

- Online Instructor: Must be available to deliver live online training sessions from around 9:00 AM to 5:00 PM Saudi Arabia time (AST).

Schedule and Contract Details

• Job Type: Fixed-term contract.
• Program Duration: 6 Weeks per cohort (multiple cohort per year)
• Expected Program Start Date: Around Nov 2026
• Instructor Availability: Availability may be required starting around Nov 2026 for onboarding, preparation, and program setup.
• Schedule: Final teaching schedule will depend on the program structure and delivery format.
• Contract details and instructional expectations: To be discussed during the interview process.

Application question(s):

• Are you willing and able to travel to Riyadh, Saudi Arabia, if required for this role?
• Are you available to teach between 9:00 AM and 5:00 PM Riyadh time (Arabia Standard Time, UTC+3), as required?
• Please briefly describe your previous teaching or training experience, including the subjects you taught, your target audience, and whether the instruction was delivered online or in person.

Work Location: Remote