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.