Analyst Programmer/System Analyst | AI Project

Analyst Programmer/ System Analyst | AI project

Key Responsibilities

• Design, build, and maintain end to end web applications (frontend, backbend, and database) with a strong focus on AI driven and GenAI 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 multiagent 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.