Artificial Intelligence Engineer

Role Overview

• Work set-up: Hybrid 3x / RTO 2x per week | Eton, Centris
• Work shift: Nightshift

This role focuses on building and deploying AI/ML solutions within enterprise data ecosystems. Key responsibilities include developing ML models and GenAI/LLM solutions (RAG, prompt engineering), integrating AI into data pipelines and platforms like Fabric and Databricks, ensuring production readiness (monitoring, performance), translating AI outputs into business insights, and upholding Responsible AI governance—all within an Agile delivery framework.

Technical Skills span

• ML Engineering : model lifecycle, feature engineering, training/deployment
• Cloud AI & Data Platforms : Azure AI/OpenAI, Microsoft Fabric, Databricks (MLflow, Delta Lake), Lakehouse architecture
• Data Engineering : Python/SQL, pipelines, orchestration
• MLOps : CI/CD, versioning, monitoring, observability
• Tooling : Azure DevOps, Git

• Soft Skills include analytical problem-solving, stakeholder communication, cross-team collaboration, documentation discipline, and adaptability in fast-paced Agile/AI environments.
• Domain Knowledge covers enterprise data platforms, ServiceNow, data governance/compliance, and Responsible AI principles (fairness, transparency, bias mitigation, auditability).

Non-Negotiable Requirements

• At least 2 years of equivalent work experience
• Finished a bachelor's degree in any specialization