Key Responsibilities
- Design, build, and maintain end-to-end web applications (front-end, backbend, and database) with a strong focus on AI-driven and GenAI-enabled products, ensuring scalability, performance, and security.
- Develop and operate CI/CD pipelines (e.g. GitLab CI, Jenkins) covering automated testing, artifact management, security scanning, and multi-environment deployments.
- Collaborate closely with data scientists, AI engineers, and product teams to design, implement, and deliver AI-powered features, including chatbots, RAG pipelines, and agent-based systems.
- Integrate LLM-based solutions into production web applications, including prompt orchestration, retrieval-augmented generation (RAG), and multi-agent LLM workflows to enhance user experience and business outcomes.
- Participate in the design and delivery of a new RAG platform, including document ingestion, vector search, orchestration, and response evaluation.
- Identify performance bottlenecks, bugs, and architectural limitations, and proactively propose and implement system improvements.
- Contribute to project planning and estimation, translating business requirements into technical solutions and delivery timelines.
- Maintain clear and concise technical documentation, including architecture, development standards, and deployment processes.
- Stay current with emerging trends in AI, GenAI, LLM orchestration, and modern web technologies, and apply them where appropriate.
Qualifications & Experience
- Bachelor's degree in Computer Science, Information Technology, Software Engineering, or a related discipline.
- 4+ years of hands-on experience in fullback JavaScript development.
- Strong proficiency in frontend technologies (HTML, CSS, JavaScript / TypeScript, React or Angular) and backend development (Node.js).
- Demonstrated experience delivering AI or Generative AI projects, such as chatbots, knowledge assistants, or AI-powered products in production.
- Solid hands-on experience with LLMs, including RAG architectures and multiagent LLM systems using frameworks such as LangChain, LlamaIndex, LangGraph, or similar.
- Familiarity with monitoring and observability tools (Grafana, Loki, Prometheus) will be a plus.
- Experience with cloud platforms (AWS and/or Azure) and familiarity with DevOps and CI/CD practices.
- Working knowledge of containerisation and orchestration, including Docker and Kubernetes.