ABOUT THE ROLE
The role exists to support the engineering and delivery of AI-enabled solutions by developing application components, operationalizing validated models, and implementing data pipelines and integrations. The role contributes to technical design, testing, deployment, and resolution of escalated issues in collaboration with Applied Research, AI Businesses, and relevant technology teams.
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KEY ACCOUNTABILITIES & ACTIVITIES
Key Accountabilities
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AI Solution Engineering
- Translate approved business requirements into technical components for AI-enabled solutions in coordination with business and research teams.
- Develop and integrate application services, APIs, and AI components in line with agreed solution designs.
- Implement assigned features and resolve technical issues against delivery plans and acceptance criteria.
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Model Operationalization & Integration
- Adapt validated models and research outputs for deployment within products, platforms, and services.
- Develop model-serving interfaces and integrate inference workflows with application components.
- Validate model integration, input and output handling, and runtime behavior with research and engineering teams.
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Data Pipeline Engineering
- Develop and maintain data ingestion and transformation pipelines for assigned AI use cases.
- Implement data validation and quality checks to support reliable model inputs and processing.
- Troubleshoot pipeline failures and coordinate source-data and integration dependencies with relevant teams.
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Technical Design & Documentation
- Contribute to technical designs and component specifications aligned with approved architecture and engineering standards.
- Document interfaces, dependencies, configurations, and design decisions for assigned solution components.
- Participate in design and code reviews and implement agreed improvements.
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Testing & Solution Validation
- Develop and execute unit, integration, and performance tests for assigned AI solution components.
- Validate functionality and technical performance against approved requirements and record identified defects.
- Coordinate defect resolution and support user acceptance testing and production-readiness activities.
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Deployment & Release Support
- Prepare deployment configurations and support automated build, testing, and release workflows.
- Coordinate assigned deployment activities, environment dependencies, and rollback arrangements with relevant teams.
- Verify functionality after release and maintain deployment and operational handover documentation.
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Technical Support & Reliability
- Provide technical investigation and resolution support for escalated issues affecting assigned AI components.
- Analyze logs and service metrics to identify causes of failures or performance degradation.
- Implement approved fixes and contribute to specialist Level 3 support with relevant engineering teams.
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Delivery Coordination & Engineering Improvement
- Track assigned deliverables, technical risks, and dependencies and communicate progress to relevant stakeholders.
- Collaborate with AI Businesses and Applied Research to clarify requirements and address delivery constraints.
- Recommend improvements to reusable components, development practices, and engineering efficiency.
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Policies, Processes & Procedures
- Follow all relevant departmental policies, processes, standard operating procedures, and instructions so that work is carried out in a controlled and consistent manner.
- Comply with all relevant safety, quality, and environmental management policies, procedures, and controls to ensure a healthy and safe work environment.
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Information Security
- Comply with all relevant information security practices and standards to ensure data integrity and confidentiality.
JOB SPECIFICATIONS
Academic and Professional Qualifications
- Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, Artificial Intelligence, or a related field.
- Relevant certifications in software development, cloud platforms, or machine learning engineering are considered an advantage.
Years and Nature of Experience
- 2–4 years of relevant experience in software engineering, AI solution development, model deployment, or data pipeline engineering.
