Job Description - Analyst Programmer/System Analyst | AI Project
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.
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