Junior Artificial Intelligence Engineer

Job Description

A Junior AI Engineer in this specific context focuses on the foundational "heavy lifting" of the AI lifecycle. Your role is to assist in the validation of legacy data—cleaning and labeling "dark data"—and helping integrate modern AI models into our global workflow product to automate IT operations.

You will support the Senior AI Engineers in bridging the gap between legacy systems and next-generation product features. This is a highly technical, hands-on role where you will learn to build data pipelines that feed into real-world, global AI applications.

Key Responsibilities

• Data Archeology & Cleaning: Assist in extracting and preprocessing unstructured data from legacy logs, tickets, and databases to create high-quality training sets.
• Model Implementation: Support the deployment and fine-tuning of machine learning models (e.g., NLP for ticket classification or time-series for predictive maintenance).
• Testing & Validation: Conduct rigorous testing of AI outputs to ensure accuracy and fairness across different global regions and user languages.
• API & Integration: Build and maintain the "plumbing" (APIs) that connects AI model outputs to the front-end IT workflow product.
• Documentation: Maintain detailed records of data lineage and model versions to ensure compliance with global data standards like GDPR.
• Continuous Learning: Stay current on emerging Generative AI trends and suggest ways to apply them to legacy data challenges

Qualifications

Technical Skills

• At least 2 years of software engineering experience, including strong hands-on AI agent system development experience
• Education: Bachelor’s degree in Computer Science, Data Science, or Mathematics. Relevant AI Certifications are a plus.
• Programming: Strong proficiency in Python (specifically libraries like Pandas, NumPy, and Scikit-learn).
• Data Handling: Solid understanding of SQL and experience with data extraction from relational databases.
• Foundational ML: Basic knowledge of Supervised/Unsupervised learning and experience with GitHub for version control.
• Tooling: Familiarity with Jupyter Notebooks and basic exposure to cloud environments (AWS, Azure, or GCP).

Soft Skills

• Persistence: A high tolerance for "messy" data and the patience required for data mining legacy systems.
• Global Collaboration: Ability to work effectively in an Agile/Scrum environment with teammates across multiple time zones.
• Analytical Curiosity: A desire to understand the "why" behind IT workflow patterns, not just the "how" of the code.

Additional Information

Why Join Us?

• Build enterprise AI systems used by hundreds of thousands of users worldwide
• Work on large-scale Agentic AI and AI-native workflow transformation initiatives
• Collaborate with global Product, Engineering, and AI teams
• Solve complex real-world enterprise AI challenges with measurable business impact
• Competitive compensation and 13th-month bonus
• Premium healthcare and accident insurance
• Flexible and international working environment