Principal AI Developer
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Key skills for this role
About the Role
Insight is looking for a Principal AI/ML Engineer to provide technical leadership across the design, development, deployment and continuous improvement of enterprise-grade AI and machine learning solutions.
Key Skills for This Role
Responsibilities
- Lead the design, development and deployment of scalable AI/ML solutions, taking ownership of the full lifecycle from discovery to production delivery and continuous improvement
- Define and govern AI/ML architecture, engineering standards and best practices
- Design, build and optimise machine learning, deep learning and generative AI solutions
- Drive the adoption of MLOps practices, including CI/CD, model versioning, monitoring, observability, performance optimisation and lifecycle management
- Collaborate closely with business stakeholders, product teams, architects, data engineers and software engineers to translate requirements into practical AI driven solutions
- Provide technical leadership and mentorship to engineers
- Lead technical discovery activities, proof of concepts and architecture assessments
- Ensure robust documentation, governance and responsible AI principles are embedded throughout the delivery lifecycle
- Stay current with emerging AI technologies, frameworks and industry trends
Requirements
- Extensive experience delivering AI/ML solutions in production environments
- Strong Python expertise and experience with frameworks such as PyTorch, TensorFlow and Scikit learn
- Deep understanding of machine learning, deep learning and Generative AI technologies
- Experience with Azure, AWS or GCP
- Strong knowledge of MLOps, CI/CD, testing and software engineering best practices
- Proven experience leading technical teams and influencing architecture decisions
Full Job Posting
Role Overview
- We are looking for a Principal AI/ML Engineer to provide technical leadership across the design, development, deployment and continuous improvement of enterprise grade AI and machine learning solutions.
- The Principal AI/ML Engineer will work closely with data scientists, software engineers, cloud engineers, architects, product teams and senior stakeholders to translate complex business problems into scalable, secure and measurable AI/ML solutions.
Key Responsibilities
- Lead the design, development and deployment of scalable AI/ML solutions, taking ownership of the full lifecycle from discovery and experimentation through to production delivery and continuous improvement.
- Define and govern AI/ML architecture, engineering standards and best practices, ensuring solutions are secure, maintainable, cost effective and aligned with wider business and technology strategies.
- Design, build and optimise machine learning, deep learning and generative AI solutions, selecting the most appropriate tools, frameworks and approaches to solve complex business challenges.
- Drive the adoption of MLOps practices, including CI/CD, model versioning, monitoring, observability, performance optimisation and lifecycle management.
- Collaborate closely with business stakeholders, product teams, architects, data engineers and software engineers to translate requirements into practical AI driven solutions that deliver measurable value.
- Provide technical leadership and mentorship to engineers, supporting capability development, design reviews, knowledge sharing and the adoption of engineering best practices.
- Lead technical discovery activities, proof of concepts and architecture assessments, helping shape AI strategy and identify opportunities where AI can improve business outcomes.
- Ensure robust documentation, governance and responsible AI principles are embedded throughout the delivery lifecycle, supporting transparency, compliance and operational excellence.
- Stay current with emerging AI technologies, frameworks and industry trends, evaluating their potential application and guiding the organisation's adoption of new capabilities
Required Experience
- Extensive experience delivering AI/ML solutions in production environments.
- Strong Python expertise and experience with frameworks such as PyTorch, TensorFlow and Scikit learn.
- Deep understanding of machine learning, deep learning and Generative AI technologies.
- Experience with Azure, AWS or GCP.
- Strong knowledge of MLOps, CI/CD, testing and software engineering best practices.
- Proven experience leading technical teams and influencing architecture decisions.
Location
- Abu Dhabi HQ Hybrid Model
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