Software Engineering Professional 2, AI Engineering
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Job Description
Design, develop, modernize, and support enterprise applications using AI-enabled software engineering practices.
• Drive legacy-to-modern technology transformation through application modernization, API-led integration, Microservices, and Micro Frontend architectures.
• Apply AI tools across the SDLC to improve development productivity, software quality, testing, documentation, and delivery efficiency.
• Integrate AI capabilities into business and customer-facing applications to enhance user experience and operational effectiveness.
• Support AI Ops, automation, observability, and operational excellence initiatives to improve application reliability and service performance.
• Collaborate with architects, product owners, engineers, and business stakeholders to deliver scalable, secure, and maintainable solutions.
• Contribute to solution architecture, engineering standards, security, compliance, and software quality best practices.
• Drive continuous improvement through automation, innovation, technical debt reduction, and adoption of emerging technologies.
• Work within Agile teams to prioritize features, modernization initiatives, and business value delivery.
Essential Skills / Experience
Functional experience/skills
• Understanding on Application Development, Application Modernization, or Digital Transformation initiatives.
• Experience working across the full Software Development Lifecycle (SDLC).
• Strong stakeholder management, communication, collaboration, and problem-solving skills.
• Ability to translate business requirements into effective technical solutions.
• Customer-focused mindset with a passion for innovation and continuous improvement.
Technical experience/skills
• Experience in Java, Spring Boot, REST APIs, Microservices, and Micro Frontend architectures.
• Experience designing, developing, and integrating enterprise-scale applications and services.
• Experience delivering legacy-to-modern technology transformation initiatives.
• Strong understanding of software architecture, integration patterns, scalability, security, resilience, and performance optimization.
• Experience with CI/CD, automated testing, DevSecOps, and modern engineering practices.
• Ability to design and develop secure, scalable, and maintainable software solutions.
AI Engineering Experience
• Strong understanding of AI and Generative AI concepts, including LLMs, SLMs, Agentic AI, Prompt Engineering, RAG, AI Ops, and enterprise AI adoption patterns.
• Experience applying AI tools to improve engineering productivity, software quality, modernization, automation, and developer experience.
• Experience using AI-assisted engineering tools such as GitHub Copilot, Amazon Q, Kiro, Cursor, or similar platforms.
• Experience integrating AI-powered capabilities into applications and engineering workflows.
• Understanding of Responsible AI, AI Governance, and Model Evaluation principles.
Learning Agility & Innovation
• AI-driven mindset with a passion for leveraging emerging technologies and AI tools to accelerate delivery and innovation.
• Quick learner with the ability to rapidly acquire new technical skills, frameworks, and technologies using AI-assisted learning approaches.
• Adaptable and self-driven, with the ability to work across diverse technologies and transformation programmes.
• Strong curiosity, continuous learning mindset, and enthusiasm for adopting new technologies and engineering practices.
Colleague Experience
• Strong relationship skills – both internal/external.
• Strong communications skills with the ability to communicate at all levels of the organisation – to both technical and business audiences.
• Ability to understand various business perspectives as part of a Global organisation.
Problem Solving
• Strong troubleshooting, analytical thinking, and root cause analysis skills.
• Ability to solve complex engineering and business challenges using innovative and data-driven appr