AI Developer

The AI Developer is responsible for designing, building, deploying, and supporting AI-powered solutions that deliver measurable business value across core business functions. This role combines software engineering, cloud infrastructure, MLOps, and Generative AI expertise to create scalable, production-ready applications and services.
Working closely with product teams, engineers, and business stakeholders, the AI Developer will own initiatives from concept through deployment, ensuring solutions are secure, reliable, maintainable, and aligned with business objectives.
The ideal candidate is highly hands-on, passionate about building real-world AI solutions, and experienced in deploying AI, machine learning, and Generative AI applications in cloud environments using Azure and modern DevOps practices.

This position is remote for Brazil.

• Bachelor's degree in Computer Science, Data Science, Software Engineering, Data Analytics, or related field.
• Strong Python development experience.
• Experience building and deploying AI or machine learning solutions into production.
• Experience with cloud platforms (Azure preferred).
• Experience with Azure DevOps and CI/CD pipeline development.
• Experience with Infrastructure as Code (IaC).
• Experience with MLOps practices and model lifecycle management.
• Experience deploying and supporting scalable distributed systems.
• Experience working with APIs and enterprise system integrations.
• Experience with Docker, Kubernetes (K8s), and Helm.
• Understanding of software architecture, design patterns, and engineering best practices.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.
• Experience working within Agile product development environments.

Preferred Qualifications

• Experience with:
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Agentic AI frameworks
• Generative AI applications
• Document Intelligence solutions
• Azure certifications.
• Experience designing enterprise AI platforms and architectures.
• Experience implementing AI evaluation frameworks and experimentation methodologies.
• Knowledge of responsible AI, security, governance, and compliance practices.
• Experience mentoring or providing technical guidance to other engineers.

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AI Solution Development

• Design, develop, deploy, and maintain production-ready AI and machine learning solutions.
• Translate business challenges into scalable AI-enabled applications and services.
• Build and integrate AI capabilities into enterprise systems and business workflows.
• Develop Generative AI solutions leveraging LLMs, Retrieval-Augmented Generation (RAG), and Agentic AI frameworks.
• Implement document intelligence and document-to-data processing pipelines.

Software Engineering

• Develop clean, maintainable, and well-tested Python applications following software engineering best practices.
• Apply object-oriented design principles and scalable architecture patterns.
• Contribute to reusable frameworks, libraries, and technical standards.
• Design and support distributed and cloud-native applications.

Cloud, DevOps & MLOps

• Build and maintain CI/CD pipelines for AI applications and supporting infrastructure.
• Implement Infrastructure as Code (IaC) practices.
• Deploy, monitor, and manage AI models and services in production environments.
• Configure cloud monitoring, logging, alerting, dashboards, and observability tools.
• Support model lifecycle management, performance monitoring, and operational reliability.
• Manage containerized solutions using Docker, Kubernetes, and Helm.
• Leverage Azure cloud services to build scalable AI platforms and solutions.

Evaluation & Continuous Improvement

• Implement testing, evaluation, and experimentation frameworks for AI solutions.
• Measure solution effectiveness through defined business and technical metrics.
• Apply A/B testing and other evaluation methodologies where appropriate.
• Continuously optimize solutions based on monitoring, feedback, and business outcomes.

Collaboration & Ways of Working

• Partner with cross-functional teams to deliver business-aligned AI solutions.
• Communicate complex technical concepts to both technical and non-technical audiences.
• Participate in architecture reviews, solution design sessions, and technical discussions.
• Support and mentor team members through knowledge sharing and collaboration.
• Demonstrate strong alignment with UL Solutions' Ways of Working, fostering trust, accountability, and continuous improvement.