The AI Software Engineer is responsible for designing, developing, implementing, and maintaining AI-enabled software applications that support business and manufacturing operations. The position works closely with AI Architects, Data Engineers, Manufacturing Teams, and Digital Transformation leaders to build intelligent solutions using Machine Learning, Generative AI, cloud technologies, and enterprise data platforms. This role contributes to the development of scalable AI software products, data pipelines, APIs, and predictive models while supporting deployment, monitoring, and continuous improvement activities. The AI Software Engineer serves as a key contributor to Industry 5.0 and Industry 6.0 initiatives, helping transform operational data into actionable business insights through innovative AI-driven solutions. Main Responsibilities AI Software Development  Develop AI-enabled software applications and intelligent business solutions.  Build and maintain Machine Learning and data processing pipelines.  Develop APIs and backend services that support AI products and digital applications.  Participate in software architecture implementation following engineering standards and best practices. AI Model Development & Deployment  Support the development, training, testing, and deployment of Machine Learning models.  Assist in implementing Generative AI solutions and Large Language Model (LLM) use cases.  Monitor model performance, accuracy, and reliability in production environments.  Support MLOps processes including model deployment, monitoring, and lifecycle management. Data Integration & Analytics  Integrate manufacturing, operational, and enterprise data sources.  Perform data preprocessing, cleansing, validation, and transformation activities.  Maintain data quality, consistency, and accessibility across platforms.  Support business intelligence, analytics, and dashboard development initiatives. Collaboration & Continuous Improvement  Collaborate with AI Architects, Data Engineers, Manufacturing Teams, and Business Stakeholders.  Participate in Agile ceremonies, sprint planning, and technical reviews.  Contribute to digital transformation and continuous improvement initiatives.  Support troubleshooting, incident resolution,



and software maintenance activities. Innovation  Research emerging AI technologies, frameworks, and industry trends.  Support proof-of-concept (PoC) and pilot projects involving AI and advanced analytics.  Recommend software, data, and process improvements that enhance operational performance. Responsibilities
• Software Engineering: Expert in modern programming languages, clean code practices, SOLID principles, design patterns, concurrency, refactoring, technical debt management, Git workflows, and large-scale system development.
• AI Application Development: Builds solutions using LLMs, prompt engineering, structured outputs, tool/function calling, RAG architectures, embeddings, vector databases, and AI agent frameworks.
• LLM Engineering: Understands transformer architectures, tokenization, context management, model selection, inference optimization, fine-tuning techniques, and deployment of both open-source and commercial models.
• AI Agents & Automation: Develops intelligent agents with memory, state management, tool integration, workflow orchestration, human-in-the-loop controls, security boundaries, and enterprise integrations.
• Machine Learning & Data Engineering: Applies practical ML techniques, develops training and inference pipelines, manages structured and unstructured data, and creates reliable data processing ecosystems.
• API & System Integration: Connects applications through REST, GraphQL, gRPC, event-driven architectures, messaging platforms, authentication systems, and enterprise services.
• Cloud & Platform Engineering: Designs and deploys solutions on AWS, Azure, or GCP using containers, Kubernetes, serverless services, managed databases, monitoring, and security controls.
• MLOps & LLMOps: Implements CI/CD pipelines, model lifecycle management, experiment tracking, automated evaluations, monitoring, version control, and controlled releases.




• Testing & Evaluation: Ensures quality through unit, integration, end-to-end, performance, AI workflow, and model evaluation testing, including hallucination detection and regression analysis.
• Security & Governance: Applies secure coding practices, OWASP standards, agent security controls, prompt injection protection, data privacy safeguards, and access management.
• Observability & Performance: Monitors systems using logging, tracing, metrics, cost tracking, and optimization techniques to maximize reliability and efficiency.
• System Design & Architecture Support: Designs scalable components, evaluates technical trade-offs, identifies risks, documents decisions, and aligns implementations with enterprise architecture.
• Troubleshooting & Operations: Diagnoses and resolves application, infrastructure, model, and production issues through systematic root cause analysis.
• Technical Leadership: Mentors developers, performs code reviews, owns critical components, leads technical initiatives, communicates risks effectively, and drives engineering excellence. Qualifications Education  Bachelor’s Degree in Computer Science, Software Engineering, Information Technology, Artificial Intelligence, Data Science, or related field.  Certifications in AI, Cloud Technologies, Data Engineering, or Software Development are a plus. Experience  3+ years of experience in software development, Artificial Intelligence, Machine Learning, or related technical roles.  Experience developing cloud-based applications and enterprise software solutions.  Experience working with Python and AI/ML frameworks.  Experience integrating APIs, databases, and cloud services.  Basic understanding of DevOps and MLOps practices.  Experience in manufacturing, Industry 5.0, or smart factory environments is preferred. Technical Skills Artificial Intelligence & Machine Learning  Machine Learning Model Development.  Deep Learning Fundamentals.  Generative AI Concepts.  Large Language Models (LLMs).  Model Training and Evaluation.  AI Solution Deployment and Monitoring. Programming & Software Development  Python Development.  Object-Oriented Programming.

📌 AI Software Engineer-Planta Ford Irapuato
🏢 Ford Motor
📍 Irapuato