Principal AI Engineer @ Opentext

OPENTEXT
OpenText is a global leader in information management, where innovation, creativity, and collaboration are the key components of our corporate culture. As a member of our team, you will have the opportunity to partner with the most highly regarded companies in the world, tackle complex issues, and contribute to projects that shape the future of digital transformation.

Title: Principal AI Engineer

Bringing structure to the unstructured by unleashing the power of informationENABLING THE DIGITAL WORLDOpenText enables the digital world by simplifying, transforming, and accelerating enterprise information needs, on premises or in the cloud. We embrace all things digital and are committed to being the Best Place to Work for our Employees in over 140 locations around the world.We obsess over our customers to ensure they are wildly successful in embracing the Digital World. Our customers entrust us with their most important information, we need to be their most trusted partner. What we do, we do well. What we create, we do purposefully to impact the world. If you believe in this and are passionate about enabling the Digital World then let OpenText turn your career vision into reality.

About the Role

We are seeking a seasoned Data Engineer with 1012 years of experience to lead the design and implementation of robust data pipelines, AI/ML-driven systems, and enterprise-ready data science solutions. The ideal candidate will have deep expertise in Generative AI, Machine Learning, and Python, along with a proven track record of delivering scalable data projects in complex environments.

What you'll do

• Architect and deploy enterprise-grade data pipelines that integrate Generative AI and Machine Learning models to solve business problems.
• Conduct research on the latest innovations in AI/ML and quickly build proof-of-concepts (PoCs) to validate new ideas.
• Apply advanced Data Science fundamentals to ensure data quality, feature engineering, and model interpretability.
• Design and optimize data infrastructure (batch/real-time) for performance, reliability, and scalability.
• Implement MLOps practices to automate model training, deployment, and monitoring.
• Mentor junior engineers and drive best practices in coding, testing, and system design.
• Stay updated with emerging trends in AI/ML, data engineering, and cloud technologies.

You are good at

• 10-12 years of hands-on experience in data engineering, with a focus on enterprise-ready data science projects.
• Expertise in Generative AI tools/frameworks (e.g. AI Agentic frameworks) and their integration into production systems.
• Ability to research emerging AI/ML trends, rapidly develop proof-of-concepts (PoCs) & drive innovation.
• Strong foundation in Machine Learning (supervised/unsupervised learning, NLP, neural networks) and Data Science concepts (statistics, data modeling).
• Proficiency in Python and libraries (Pandas, NumPy, TensorFlow/PyTorch, scikit-learn).
• Prior experience in AI model deployment, fine-tuning, and optimization.
• Experience with programming best practices (OOP, version control, CI/CD) and distributed systems.
• Knowledge of cloud platforms (AWS/Azure/GCP)
• Strong analytical, problem-solving, and communication skills.
• Experience building microservices and orchestrating them via Docker/Kubernetes.
• Familiarity with MLOps tools (MLflow, Kubeflow) and monitoring frameworks.
• Background in the IT domain (e.g., fintech, healthcare, e-commerce).
• Familiarity with APIs and real-time data processing frameworks.
• Good to have experience in Java programming.