M38 - Full Stack Engineer (Pega, AI)

Overview

We 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.

Responsibilities

• Analyse 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.

Requirements

• Degree or Diploma in Computer Science, Information Technology, Computer Engineering, Electronics Engineering, or a related discipline.
• Technical Skills
• Strong 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 Bedrock

Solid understanding of Large Language Models (LLMs), including:

• Tokenisation
• Context windows
• Prompt engineering

Hands-on experience building AI-powered applications and agentic workflows using frameworks such as:

• LangChain
• LangGraph
• LlamaIndex

Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions, including:

• Vector databases (e.g. Pinecone, Weaviate, FAISS)
• Embedding models and retrieval strategies
• Integration with enterprise knowledge sources

Platform & Infrastructure

Experience in one or more of the following areas:

• Agile software development methodologies
• CI/CD pipelines and DevOps practices
• Cloud platforms such as AWS or GCP
• Serverless architectures
• Docker and containerisation technologies

Preferred Experience

• 2–5 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.