• Build and deploy custom model context protocol (MCP) connectors for new and existing services • Design and implement custom agentic workflows using cloud AI platforms • Develop server-side application logic and APIs that integrate AI capabilities with existing enterprise systems • Contribute to the development and maintenance of reusable AI component libraries and shared code infrastructure • Write high-quality code, applying best practices, coding standards, and design patterns for AI systems • Participate in the entire AI solution lifecycle, including requirement gathering, design, development, testing, and deployment, using an agile, iterative process • Participate in code reviews and ensure code quality through effective testing strategies and security validation • Collaborate with infrastructure teams, security teams, developers, designers, testers, project managers, product managers, and project sponsors • Communicate tasking estimation and progress regularly to a development lead and product owner through appropriate tools • Ensure seamless integration with backend systems, cloud services, databases and messaging systems • Team with other developers, fostering a culture of continuous learning and professional growth in AI engineering

• Attend and complete the Flatiron School Data Science Bootcamp as part of the apprenticeship • Contribute to software projects for your host company • Write clean, maintainable and testable code using modern frameworks and tools • Collaborate in sprint-based workflows and participate in code reviews • Support feature development, debugging, documentation, and QA processes • Build your portfolio of production-level work while growing your technical and collaborative skills • Receive ongoing mentorship from senior developers and product leaders

• Attend and complete the part-time Data Science Bootcamp as part of the apprenticeship • Contribute to software projects for your host company • Write clean, maintainable and testable code using modern frameworks and tools • Collaborate in sprint-based workflows and participate in code reviews • Support feature development, debugging, documentation, and QA processes • Build your portfolio of production-level work while growing your technical and collaborative skills • Receive ongoing mentorship from senior developers and product leaders

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role supports high-impact collaborations with leading AI teams focused on improving how conversational AI models reason about complex engineering concepts across multiple disciplines. - Write and refine prompts that guide AI models in engineering-related scenarios - Evaluate AI-generated responses for technical accuracy and applied reasoning - Verify engineering claims using domain expertise and authoritative sources - Annotate responses by identifying strengths, gaps, and conceptual inaccuracies - Assess clarity, structure, and appropriateness of explanations for different audiences - Apply structured evaluation guidelines and benchmarking standards - Ensure model responses align with expected system behavior and engineering logic Qualifications - PhD in Engineering or a closely related technical discipline - Expertise in one or more of the following areas: - Mechanical & Physical Systems Engineering - Electrical, Electronic & Computer Engineering - Chemical, Materials & Process Engineering - Civil, Environmental & Infrastructure Engineering - Strong experience using large language models (LLMs) - Excellent technical writing and explanation skills - Strong analytical reasoning and attention to detail - Ability to identify subtle technical inaccuracies in model outputs Requirements - Applied research or industry engineering experience - Experience with RLHF, model evaluation, or AI data annotation - Experience teaching or mentoring technical concepts - Familiarity with evaluation rubrics or structured review frameworks What Success Looks Like - Identifying technical inaccuracies or flawed reasoning in engineering outputs - Improving the rigor and clarity of AI explanations - Producing consistent evaluation artifacts that strengthen model performance - Helping ensure AI systems provide reliable engineering guidance Why This Opportunity - Contribute directly to improving the reasoning capabilities of advanced AI systems - Apply deep engineering expertise to real-world AI development - Work with cutting-edge AI labs and research teams - Flexible remote work with competitive compensation Contract Details - Independent contractor role - Fully remote with flexible scheduling - Compensation: $73.29/hr - Weekly payments via Stripe or Wise - Projects may expand depending on performance and project needs About the Platform This opportunity is available through a leading AI-driven work platform.