AI Engineering Mentor

This is a fully remote position, open to applicants in United Kingdom, +1 more country.

📋 Description

• Facilitate discussions within an online community, linking weekly technical learning and building activities to practical AI engineering applications.

• Design and conduct three 60-minute live sessions focused on the practical application of learning topics within the industry.

• Offer structured 30-minute one-on-one sessions to assist learners with industry context and career guidance.

• Share real-world examples and insights gained from developing and operating LLM-based systems in production settings.

• Assist learners in navigating pathways into AI engineering, understanding employer expectations, establishing portfolio credibility, and engaging in professional engineering practices.

• Collaborate with colleagues in delivery to identify learner concerns, exchange feedback, and provide insights on program content and learner engagement.

• Aid learners in connecting RAG, retrieval design, agent architectures, evaluation, monitoring, responsible AI, and production engineering with real-world workplace scenarios.

• Tailor guidance for learners with diverse backgrounds, including career changers, seasoned coders, and practicing software engineers.

• Maintain academic assessment boundaries by refraining from grading, directly correcting assessed work, or offering detailed guidance on assessed tasks.

⛳️ Requirements

• Proven professional software engineering experience, including hands-on work in building and operating LLM-based systems in a production environment.

• Current experience in roles such as AI Engineer, AI Application Engineer, Senior or Staff Software Engineer, Machine Learning Engineer, Technical Lead, Principal Engineer, Architect, or AI Engineering Consultant.

• Practical knowledge of LLM APIs, function calling, RAG, retrieval design, agent architectures, evaluation techniques, and optimization for cost or latency.

• Strong fundamentals in production engineering, encompassing testing, CI/CD, containerization, monitoring, and incident response.

• Familiarity with responsible AI practices in practical deployment contexts, including governance, auditability, bias assessment, human oversight, and regulatory considerations.

• Experience in AI-assisted software development, with an understanding of common failure modes and strategies for verifying AI-generated code.

• Proven ability to articulate complex technical concepts clearly to individuals with varying levels of technical expertise.

• Excellent communication, facilitation, mentoring, and relationship-building skills, with the discernment to guide learners through uncertainty rather than providing overly prescriptive responses.

• Comfort with online learning and communication technologies.

• Prior experience in teaching, mentoring, facilitation, or online learning is preferred.

• A master's degree is preferred but not mandatory.

🏝️ Benefits

• A collaborative, people-focused performance culture.

• Opportunities for growth in a dynamic environment.

• The chance to contribute current industry insights to the training of emerging AI engineering professionals.

• Flexible participation in a remote learning environment, depending on the role's requirements.