Full-Stack Engineer
About the job
About the Full-Stack Engineer role
Key Responsibilities:
- Analyze the client needs, scope the problem and develop business case to address the problem
- Document requirements, source and evaluate alternatives, and recommend solution that best fits the client needs
- Work with clients and app vendor on the solutions and design to seek clarification and acceptance
- Design, develop and deliver working software applications to delight customers
- Improve software quality using XP practices such as code review and unit testing
- Prepare architectural and other technical documents
- Assist BA on user stories elaboration
- Assist QA on test automation and bug fixes
- Assist DevOps on build and release automation
- Work with client users to ensure smooth deployment and adoption of new solution
- Assess business needs for service requests and the impact of enhancements to the system
- Assess problem resolution approach and implement effective service recovery of ICT incidents and establish systems and processes to prevent recurrence of the same incident
- Understand the IT management policy, quality management policy and security guidelines to ensure the development processes, procedures and system are designed to comply with these policies and guidelines
Requirements:
- Degree or Diploma in Computer Science, Computer or Electronics Engineering, Information Technology, or related disciplines
- Strong proficiency in Python, including writing scripts, handling data structures, and building robust backend APIs using frameworks such as FastAPI
- Solid understanding of LLM fundamentals, including tokenisation, context windows, and API integrations with providers such as OpenAI, Anthropic, Gemini, and AWS Bedrock, along with practical experience in prompt engineering
- Hands-on experience building agentic workflows and multi-step AI processes using orchestration frameworks such as LangChain, LangGraph, or LlamaIndex
- Demonstrated ability to design and implement Retrieval-Augmented Generation (RAG) systems, including working with vector databases (e.g. Pinecone, Weaviate, FAISS) and embedding techniques to enable AI models to access and reason over external data sources
- Experience designing AI agent systems, including equipping models with tools, memory, and the ability to plan and execute multi-step actions autonomously
- 2 to 5 years of experience in the Pega application platform will be a strong advantage, as our main application is built on Pega. Experience integrating AI and LLM capabilities into Pega workflows is particularly valued
- Hands-on experience in at least one full project development life cycle in Pega will be an added advantage
- Experience in one or more of the following processes and infrastructure areas:
- Agile processes and practices
- Continuous integration and continuous deployment (CI/CD)
- Cloud and PaaS platforms such as AWS or GCP
- Serverless frameworks
- Docker and container technologies
- Familiarity with unit testing and software quality practices
Preferred Qualifications:
- Consulting or Business Analysis experience
- Prior experience in system solutioning and development for mid to large-scale IT projects
- Knowledge of web services, REST APIs, SFTP, and security concepts for system interfaces
- Experience in requirement and workshop facilitation, and documentation of user requirements into Agile user stories and acceptance criteria
- Experience defining UAT test scenarios and facilitating SIT and UAT testing
- The following personal traits will be an added advantage: self-driven and independent, strong problem-solving and analytical skills, good communication and interpersonal skills, and strong presentation and listening skills
