Artificial Intelligence Engineer

Responsibilities

- Leading the development and implementation of innovative software solutions to drive digital transformation
- Designing, coding, and testing applications that enhance business performance and user experience
- Applying systems thinking to identify underlying problems and opportunities within software engineering projects
- Directing teams through complex and ambiguous situations, maintaining composure and focus
- Crafting and conveying clear, impactful messages that tell a holistic story to stakeholders
- Validating outcomes with clients, sharing alternative perspectives, and acting on feedback
- Developing and evolving skills to stay relevant in the rapidly changing technology landscape
- Initiating open and honest coaching conversations to foster team growth and effectiveness
- Making informed decisions to resolve issues that hinder team performance
- Modeling and reinforcing professional and technical standards in line with the firm's code of conduct
- Utilizing programming languages such as Python and React Native to create scalable solutions
- Implementing Continuous Integration/Continuous Delivery (CI/CD) practices to streamline software development processes
- Collaborating with enterprise application architecture teams to design robust software solutions

What You Must Have

- At least a Bachelor's degree
- At least 14 years of experience
- Oral and written proficiency in English required

What Sets You Apart

- Preference for at least one of the following fields of study: Artificial Intelligence, Business Analytics, Computer and Data Engineering, Computer Science, Human Computer Interaction, Industrial Engineering, Information Systems/Technology, Machine Learning, Management Information Systems, Software Engineering
- Proven leadership in architectural design and implementation

- Strategic thinking with a technical background (Python, LLM, LangGraph, LangFlow, LangChain)

- Managing cross-functional teams effectively

- Delivering AI applications using RAG, vector databases, and agent-based frameworks

- Promoting observability and optimization of AI applications

- Implementing CI/CD pipelines and observability for AI systems using tools such as GitHub Actions and MLflow

- Collaborating with engineering and data science teams

- Familiarity with AI coding tools and frameworks