AI Engineering Trainer; 1099 Contractor

At Fearless, we are seeking a 1099 contractor to serve as an AI Engineering Trainer for a 10-week intensive workforce development program focused on AI-enabled software engineering and modernization. The trainer will lead a cohort of experienced technical professionals through a structured curriculum designed by Team Fearless, combining live instruction, hands-on labs, technical demonstrations, collaborative projects, and individualized coaching. This role requires both hands-on AI engineering experience and the ability to translate complex technical concepts into practical skills.

The trainer will help participants design, develop, integrate, test, troubleshoot, and securely deploy AI-enabled and agentic AI solutions within realistic enterprise environments. Training will include AI engineering fundamentals, agentic AI, AI-assisted software development, Python, data and integration patterns, secure software delivery, responsible AI, and modernization of legacy systems. The curriculum is provided by Fearless; the trainer is not expected to develop the curriculum independently but may supplement it with additional examples, exercises, or resources that strengthen the learning experience.

This is a fully remote 1099 contractor engagement requiring 40 hours per week for 10 weeks, with work performed between 9:00 a.m. and 5:00 p.m. EST.

• Deliver live, instructor-led technical training focused on AI engineering, agentic AI, and AI-enabled software development.
• Lead hands-on labs, technical demonstrations, practical exercises, and collaborative projects that require participants to design, build, integrate, test, debug, and troubleshoot AI-enabled solutions.
• Teach and reinforce practical application of Python, AI/LLM tools and frameworks, APIs, data engineering concepts, source control, testing, and modern software delivery practices.
• Guide participants through AI-assisted engineering workflows, including code generation, testing, automation, debugging, and legacy application modernization.
• Provide instruction and coaching on prompt engineering, Retrieval-Augmented Generation (RAG), AI orchestration patterns, and agentic AI concepts as applicable to the approved curriculum.
• Reinforce secure AI integration, responsible AI practices, data governance, privacy, security, and risk mitigation throughout technical exercises and projects.
• Provide real-time technical assistance during labs and project work, including troubleshooting, debugging, code review, and problem-solving support.
• Review participant technical work and provide individualized feedback, coaching, and remediation to strengthen identified skill gaps.
• Assess participant progress through labs, assignments, knowledge checks, technical demonstrations, and capstone activities.
• Support team-based capstone work requiring participants to demonstrate an AI-enabled or agentic solution within a realistic enterprise modernization scenario.
• Collaborate with program leadership and other instructors to monitor participant progress, identify areas requiring additional reinforcement, and maintain alignment with the approved training plan.

• Minimum of 5 years of professional experience in AI/ML engineering, software engineering, data engineering, or a closely related technical discipline.
• Demonstrated hands-on experience designing, developing, deploying, troubleshooting, optimizing, or maintaining AI and/or agentic AI solutions in production or comparable enterprise environments.
• Demonstrated experience delivering technical instruction, hands-on training, developer enablement, mentoring, coaching, or workforce development for adult technical learners.
• Strong working knowledge of Python and modern AI/LLM development tools, frameworks, and engineering workflows.
• Experience with AI-enabled application development, including APIs, data integration, testing, debugging, and secure software development practices.
• Experience with generative AI and modern AI engineering patterns such as prompt engineering, RAG, AI orchestration, and/or agentic AI frameworks.
• Ability to review participant code and technical artifacts, diagnose implementation challenges, and provide actionable technical feedback.
• Experience teaching through hands-on labs, projects, demonstrations, and applied exercises rather than lecture-only instruction.
• Strong communication skills with the ability to explain complex AI and software engineering…