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Job Description
Structured overview of role & requirementsAbout This Role
Lead architecture, technical design, and implementation of large-scale AI and data platforms focusing on robustness, security, and performance.
Champion best practices in software development and cloud-based machine learning infrastructure across multiple teams, setting high standards for quality and maintainability.
Collaborate with global stakeholders to align technology roadmaps with business goals, drive adoption of modern DevOps/MLOps methodologies, and oversee end-to-end lifecycle of critical AI projects.
Minimum Requirements
Bachelor’s or Master’s degree in Computer Science, Software Engineering, AI, Machine Learning, or related field; Master’s in AI/ML/Generative AI highly desirable.
Minimum 12 years of software engineering experience including at least 5 years in senior leadership or principal engineer capacity.
Expertise in AI platforms with cloud-native architectures using AWS SageMaker, Databricks, Azure ML, or Google Vertex AI.
Proficiency in Python, Java, Scala, or Go; strong DevOps skills including Kubernetes, Docker, CI/CD pipelines; experience deploying large-scale ML models in production.
Ideal Candidate Profile
Proven technical leader capable of guiding large engineering teams through complex, ambiguous AI and software projects with strategic impact.
Experience building enterprise-scale AI/ML solutions with operational knowledge of modern ML stacks (LLMs, PyTorch, TensorFlow) and agentic AI workflows.
Demonstrated ability to influence cross-functional global stakeholders and shape technology vision in a fast-paced, agile environment.