M38 - Full Stack Engineer (Pega, AI)

OverviewWe are looking for a Full-Stack Engineer with a strong foundation in software engineering and modern AI technologies. The ideal candidate will have experience building scalable applications, integrating LLM-powered solutions, developing AI agents and RAG systems, and working across the full software development lifecycle. Experience with the Pega platform will be highly advantageous.ResponsibilitiesAnalyse business needs, identify problem statements, and recommend technology solutions to address organisational objectives.Gather, document, and validate functional and technical requirements with stakeholders.Collaborate with business users, vendors, and project teams to clarify requirements, review solution designs, and obtain stakeholder buy-in.Design, develop, test, and deploy scalable software applications that deliver a high-quality user experience.Prepare and maintain architecture diagrams, technical specifications, and system documentation.Work closely with Business Analysts to refine requirements, elaborate user stories, and define acceptance criteria.Support Quality Assurance activities, including test automation, defect analysis, and bug resolution.Partner with DevOps teams to automate build, deployment, and release processes.Drive adoption and ensure smooth deployment of new solutions through stakeholder engagement and support.Assess enhancement requests, evaluate system impacts, and recommend implementation approaches.Investigate and resolve application incidents, perform root cause analysis, and implement preventive measures to minimise recurrence.Apply software engineering best practices including code reviews, unit testing, and continuous improvement methodologies.Ensure solutions comply with IT governance, security standards, quality management policies, and organisational guidelines.RequirementsDegree or Diploma in Computer Science, Information Technology, Computer Engineering, Electronics Engineering, or a related discipline.Technical SkillsStrong proficiency in Python, including backend application development and API design using frameworks such as FastAPI.Experience designing AI agent systems with capabilities such as memory, tool usage, planning, and autonomous task execution.Familiarity with REST APIs, web services, secure file transfer (sFTP), and system integration patterns.Experience with software testing, code quality practices, and automated testing frameworks.API integration with platforms such as OpenAI, Anthropic, Gemini, and AWS BedrockSolid understanding of Large Language Models (LLMs), including:TokenisationContext windowsPrompt engineeringHands-on experience building AI-powered applications and agentic workflows using frameworks such as:LangChainLangGraphLlamaIndexExperience designing and implementing Retrieval-Augmented Generation (RAG) solutions, including:Vector databases (e.g. Pinecone, Weaviate, FAISS)Embedding models and retrieval strategiesIntegration with enterprise knowledge sourcesPlatform & InfrastructureExperience in one or more of the following areas:Agile software development methodologiesCI/CD pipelines and DevOps practicesCloud platforms such as AWS or GCPServerless architecturesDocker and containerisation technologiesPreferred Experience2–5 years of experience with the Pega platform.Experience integrating AI and LLM capabilities into Pega applications and workflows.Hands-on participation in at least one end-to-end Pega project implementation.Experience delivering medium to large-scale enterprise or government technology projects.Consulting, Business Analysis, or solutioning experience.Experience facilitating workshops, gathering requirements, and translating them into Agile user stories and acceptance criteria.Experience supporting SIT, UAT planning, execution, and stakeholder sign-off.