Software Engineer, AI-Focused -

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, automatedtesting, 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.