Software Engineer, AI-Focused - #1588

Core Responsibilities

• Work with stakeholders to assess business needs and recommend appropriate technology and implementation approaches, including build vs. buy and in-house vs. outsourced delivery.
• Design, develop, enhance and support enterprise applications deployed on-premises or in the cloud.
• Develop secure APIs, system integrations and application services.
• Build and integrate AI-enabled capabilities using LLM APIs, RAG, AI agents, tool calling and related technologies where appropriate.
• Lead assigned application development and enhancement projects from requirements gathering through testing, deployment and operational handover.
• Manage project scope, timelines, risks, dependencies, vendors and stakeholder communications.
• Coordinate system integration testing and User Acceptance Testing (UAT).
• Apply Agile, Scrum or hybrid delivery practices to support iterative development and delivery.
• Apply DevOps practices including Git, automated testing, CI/CD, containerisation, monitoring and logging.
• Deploy and support applications on AWS, Microsoft Azure and/or Google Cloud Platform.
• Monitor the performance and fitness of assigned systems and recommend improvements to reliability, efficiency and user experience.
• Evaluate emerging software, cloud and AI technologies and recommend their adoption where they provide clear business value.

Core Requirements

• Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, Information Technology or a related discipline, or equivalent practical experience.
• Minimum five years of relevant experience in software development, application delivery or enterprise system implementation.
• Strong proficiency in at least one programming language or platform, such as C#/.NET, Java or Python.
• Experience developing web applications, APIs and system integrations.
• Hands-on experience with at least one major cloud platform: AWS, Microsoft Azure or Google Cloud Platform.
• Familiarity with Git, CI/CD, automated testing, Docker, microservices and DevOps practices.
• Practical experience or exposure to AI-enabled application development, including LLM APIs, RAG, AI agents, embeddings/vector search or agentic frameworks.
• Good understanding of the full SDLC and experience managing or coordinating application delivery projects.
• Familiarity with Agile, Scrum or hybrid project delivery methods.
• Strong analytical, planning, communication and stakeholder-management skills.

Advantageous Experience

• Experience with Kubernetes, infrastructure as code or cloud-native architecture.
• Exposure to AI frameworks such as LangChain, LangGraph, Semantic Kernel, CrewAI or Model Context Protocol.
• Experience managing vendors or system integrators.
• Cloud, Agile or project management certifications.
• Experience with Design Thinking or Service Design methodologies.

Qualifications and Personal Attributes

• Bachelor's degree in Computer Science, Software Engineering, Information Technology or a related field, or equivalent practical experience.
• Strong analytical and problem-solving skills, with the ability to troubleshoot across application, integration and cloud layers.
• Clear communication and effective collaboration within cross-functional teams.
• Self-motivated, adaptable and willing to learn evolving technologies while maintaining sound engineering judgement.
• Ability to manage competing priorities and deliver effectively in an Agile or hybrid delivery environment.