Ai business analyst

Get recognition and reward working with this pioneering industry leader, as they embark on a transformative journey! As a Technical Business Analyst, you will sit at the intersection of business, engineering, and data science. You'll play a critical role in translating complex business problems into clear, actionable technical requirements that enable the delivery of scalable, production-grade AI solutions.

You will support the design and implementation of modern AI architectures, including agentic workflows, RAG pipelines, orchestration frameworks, and LLMOps processes, ensuring solutions are robust, compliant, and aligned to business outcomes.

Key Responsibilities

• Partner with product, engineering, and data science teams to define requirements for AI-native solutions across the agentic AI ecosystem
• Translate business needs into detailed technical specifications, user stories, acceptance criteria, and process flows
• Analyse systems, data sources, and integration points to support backend engineering and LLMOps design
• Contribute to the design of scalable, cloud-native AI architectures using technologies such as Vertex AI, LangChain, LangGraph, LlamaIndex, MCP, and containerised environments
• Support API design, data modelling, workflow automation, and integration requirements
• Assist with Responsible AI documentation, model governance, and risk assessments
• Facilitate workshops, backlog refinement, sprint ceremonies, and cross-team alignment
• Ensure delivery outcomes are measurable, compliant, and aligned to the client's AI-first strategy

What You Bring

• 5+ years' experience as a Technical Business Analyst, Systems Analyst, or Product Analyst
• Strong capability in writing clear, detailed technical requirements and user stories
• Experience working with AI/ML, data engineering, or cloud-native platforms
• Understanding of modern AI concepts such as RAG, embeddings, agentic workflows, vector search, LLMOps, orchestration frameworks
• Ability to collaborate effectively with software engineers and data scientists
• Experience in agile delivery and DevOps-aligned teams
• Excellent communication skills with the ability to translate between business and technical stakeholders
• Exposure to cloud platforms (GCP preferred), CI/CD pipelines, and containerised environments (Docker/Kubernetes)

Desired Skills and Experience

• AI/ML, data engineering, or cloud-native platforms
• modern AI concepts such as RAG, embeddings, agentic workflows, vector search, LLMOps, orchestration frameworks
• cloud platforms (GCP preferred), CI/CD pipelines, and containerised environments (Docker/Kubernetes)