The Role The Jr. AI Engineer is part of the Engineering AI team within CT CTO Mexico and supports the development, testing, and continuous improvement of AI solutions that help engineers work faster and deliver higher-quality results. This role contributes to Clarios' AI transformation strategy by assisting in the creation of scalable AI tools, automation capabilities, and evaluation frameworks that improve engineering productivity and innovation.

What You'll Do
(Impact Areas) AI Solution Development
- Develop and enhance AI prototype components, including prompts, retrieval workflows, integrations, and simple user interfaces.
- Reuse and extend existing AI frameworks and templates following coding and version control standards.
- Implement enhancements and fixes based on user feedback and testing results.
- Participate in demonstrations and pilot deployments with engineering teams. Testing & Solution Evaluation
- Create and maintain test datasets to validate AI solution performance.
- Execute repeatable evaluations and measure solution accuracy, usefulness, and reliability.
- Track user feedback and AI adoption metrics to support continuous improvement.
- Partner with Data Engineers to support data preparation, validation, and reporting activities. Automation & Engineering Efficiency
- Develop automation scripts to improve engineering workflows and document quality checks.
- Automate repetitive activities related to prototyping, testing, and reporting.
- Maintain tested, documented, and version-controlled automation assets. Documentation & User Enablement
- Create user guides, release notes, solution documentation, and known limitation records.
- Support engineering teams in effectively utilizing AI solutions.
- Escalate technical issues when appropriate and maintain solution traceability.




- Ensure compliance with responsible AI, information security, and data governance requirements. Collaboration & Continuous Learning
- Collaborate closely with AI Engineers, Data Engineers, and engineering stakeholders.
- Participate in engineering reviews and feedback sessions.
- Complete development plans focused on AI engineering, software quality, and engineering processes.
- Share learnings and propose innovative ideas for future AI initiatives. What Success Looks Like Success in this role will be measured through a combination of technical execution, operational excellence, and professional growth. Key Performance Indicators (KPIs)
- Assigned AI development tasks delivered on time and approved through technical reviews.
- AI solutions supported with current test datasets and documented evaluation results.
- Automation scripts successfully implemented and adopted by users.
- High-quality code demonstrated through positive reviews, adequate test coverage, and low defect rates.
- Timely support and resolution of user inquiries and issues.
- Complete and up-to-date documentation for each solution release. Strategic Outcomes
- Increased adoption and trust of AI tools within engineering teams.
- Improved productivity through automation and AI-enabled workflows.
- Reliable and scalable testing processes that support solution quality and continuous improvement. Behavioral Indicators




- Demonstrates ownership and accountability for assigned work.
- Proactively seeks opportunities to learn and improve.
- Builds credibility through responsiveness, collaboration, and quality execution.
- Consistently applies responsible AI and data governance practices. Core Competencies Technical Competencies
- AI solution development fundamentals
- Prompt engineering and LLM application knowledge
- Python programming
- Automation and scripting
- Software testing principles
- Data analysis and evaluation methodologies
- Version control and Git practices Professional Competencies
- Structured problem-solving
- Attention to detail and quality focus
- Learning agility and continuous improvement mindset
- Project execution and task management
- Collaboration and teamwork
- Written and verbal communication
- Service orientation and customer focus
- Integrity and responsible AI usage What You Bring (Qualifications) Education Bachelor's degree in Computer Science, Computer Engineering, Electronics, Mechatronics, Data Science, or a related field. Recent graduates are encouraged to apply. Experience 0-2 years of experience in software development, AI, machine learning, or data science. Internship, academic, and personal project experience will be considered. Technical Skills
- Strong Python programming skills.
- Basic knowledge of Git, SQL, APIs, and software development practices.
- Experience or exposure to Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), or AI Agents.
- Understanding of software testing concepts.
- Familiarity with AI integration tools and object-oriented programming concepts.
- Knowledge of UML.
- Experience with Microsoft 365, Power BI, or Azure is preferred. -

📌 Jr. AI Engineer (Monterrey)
🏢 Clarios
📍 Monterrey