Key Responsibilities
• Design, build, and deploy production-grade applications and services that embed AI and GenAI capabilities in a secure, scalable, and maintainable way.
• Build and evolve core engineering foundations including APIs, reusable services, cloud-native deployment patterns, CI/CD pipelines, monitoring, and operational support for AI-enabled products.
• Work closely with platform, infrastructure, data engineering, and DevSecOps teams to improve deployment velocity, runtime resilience, security controls, and engineering efficiency.
• Lead the technical direction of software engineering and AI initiatives, ensuring a balanced focus on product architecture, engineering quality, and applied AI delivery.
• Mentor software engineers and AI engineers, raising the bar on coding standards, system design, testing, delivery practices, and responsible use of AI technologies.
• Define engineering and evaluation practices that ensure software quality, model quality, reliability, performance, observability, and compliance for AI tooling and services.
• Guide the strategic adoption of AI and GenAI by identifying high-value opportunities and turning them into robust engineering outcomes that can scale across the enterprise.
• Partner with Product Management and business stakeholders to translate requirements into well-architected software solutions, AI-enabled workflows, and delivery roadmaps.
• Stay current with emerging software engineering and AI practices, continuously improving delivery approaches, technical standards, and relationships across Shell, industry, and academia.
• Contribute to technical communities of practice and centres of excellence, helping to strengthen engineering capability, reusable patterns, and responsible AI adoption.
Professional Qualifications & Skills
Educational Qualification
• Bachelor's, Master's, or PhD degree in Computer Science, Software Engineering, Engineering, Data Science, Machine Learning, or a related technical discipline.
• Minimum 8+ years of industry experience, including significant hands-on delivery across both software engineering and AI/ML-enabled product development.
Required Skills
• Strong experience delivering production-grade digital products with a balanced focus on modern software engineering and applied AI/GenAI.
• 8+ years of development experience across relevant languages, frameworks, and tooling such as Python, Java, JavaScript/TypeScript, JVM-based technologies, APIs, event-driven systems, and cloud-native platforms.
• Strong software engineering fundamentals including system design, clean code practices, testing strategies, code reviews, version control, and maintainable architecture.
• Hands-on experience building, deploying, and monitoring applications on Kubernetes and related cloud-native infrastructure.
• Experience designing and operating scalable services, APIs, microservices, or platform components with strong attention to reliability, performance, and security.
• Practical experience designing, developing, deploying, and monitoring machine learning and GenAI | Software Design, Software Engineering Management, Software Engineering Process
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