Full-Stack Engineer (AI & Intelligent Applications)

Role Overview

We are seeking a Full-Stack Engineer with strong software engineering capabilities and practical experience in AI-powered application development. The successful candidate will be involved in the full software development lifecycle, from requirements gathering and solution design to implementation, testing, deployment, and ongoing support.

This role offers the opportunity to work on modern digital solutions incorporating AI, Large Language Models (LLMs), intelligent automation, and enterprise-grade applications.

Key Responsibilities

Business & Solution Analysis

• Analyse business requirements and identify suitable technology solutions.
• Gather, document, and refine functional and technical requirements.
• Evaluate alternative approaches and recommend optimal solutions.
• Collaborate with stakeholders to clarify requirements and obtain solution acceptance.
• Assess enhancement requests and evaluate their impact on existing systems.

Application Development

• Design, develop, and deliver high-quality software applications.
• Build scalable backend services, APIs, and full-stack solutions.
• Integrate AI and LLM capabilities into business applications and workflows.
• Develop and maintain technical architecture and design documentation.
• Ensure software quality through code reviews, testing, and engineering best practices.

Quality Assurance & DevOps

• Support the development of automated testing and quality assurance processes.
• Troubleshoot defects and implement timely bug fixes.
• Contribute to CI/CD pipelines and deployment automation.
• Collaborate with DevOps teams to improve build, release, and operational processes.

Support & Operations

• Support deployment activities and user adoption of new solutions.
• Investigate system issues and implement effective resolutions.
• Improve system reliability and establish preventive measures to reduce recurring incidents.
• Ensure compliance with organisational IT governance, quality, and security standards.

Requirements

Education

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

Technical Skills

• Strong proficiency in Python development.
• Experience building backend APIs using frameworks such as FastAPI.
• Solid understanding of software engineering principles, data structures, and system design.
• Experience integrating with REST APIs and external services.
• Familiarity with software testing, debugging, and performance optimisation.

AI & Large Language Models (LLM)

• Strong understanding of LLM concepts, including:

  • Tokenisation
  • Context windows
  • Prompt engineering
  • API integration with AI platforms

• Experience working with AI platforms such as:

  • OpenAI
  • Anthropic
  • Google Gemini
  • AWS Bedrock

• Hands-on experience building AI-powered applications and workflows.

Agentic AI & RAG

• Experience developing AI agents and autonomous workflows.

• Familiarity with orchestration frameworks such as:

  • LangChain
  • LangGraph
  • LlamaIndex

• Experience implementing Retrieval-Augmented Generation (RAG) solutions.

• Knowledge of vector databases such as:

  • Pinecone
  • Weaviate
  • FAISS

• Understanding of embeddings, semantic search, and external knowledge retrieval techniques.

Enterprise Application Experience (Preferred)

• Experience with enterprise application platforms is advantageous.
• Experience integrating AI capabilities into enterprise workflows will be highly regarded.
• Exposure to at least one complete software development lifecycle project is preferred.

Cloud & Modern Engineering Practices

Experience in one or more of the following areas:

• Agile software development methodologies
• CI/CD pipelines and DevOps practices
• Cloud platforms (AWS, GCP, Azure, or equi