AI Engineering Trainer, (1099 Contractor)

Fearless•Baltimore, MD
•Remote

About The Position

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.

Requirements

  • 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 concepts to learners with varying levels of technical experience.

Nice To Haves

  • Experience developing or deploying AI solutions within federal, financial, tax-processing, or similarly regulated enterprise environments.
  • Experience applying AI-assisted engineering techniques to legacy application modernization.
  • Experience with enterprise data platforms, cloud environments, CI/CD, DevSecOps, or secure AI deployment.
  • Familiarity with Databricks, Pega, Salesforce, Palantir, or comparable enterprise platforms.
  • Experience with AI governance, responsible AI, data governance, security, privacy, and compliance requirements.
  • Experience supporting team-based technical capstones, bootcamps, apprenticeships, or accelerated workforce development programs.
  • Familiarity with Learning Management Systems (LMS) and participant progress tracking.

Responsibilities

  • 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.

Benefits

  • Competitive contract rates that reflect the expertise, experience, and value our independent contractors bring to client engagements.
  • Opportunity to contribute to mission-driven work that delivers meaningful outcomes.
  • Opportunity to collaborate alongside experienced professionals across technology, delivery, design, and organizational development.
  • Opportunity to apply your expertise to impactful client engagements.
  • Opportunity to build relationships with a values-driven organization committed to excellence.
  • Opportunity to work with a team that values autonomy, accountability, and results.
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