Technical Business Analyst - AI LAB at Datacom Connect

Technical Business Analyst – AI LAB Position: Full‑time, onsite, Wellington City, New Zealand. Overview Datacom is seeking a Technical Business Analyst with a strong AI focus to bridge the gap between cutting‑edge AI capabilities and real‑world business outcomes. The role involves shaping AI‑driven solutions, ensuring intelligent systems are designed, documented, and delivered with precision, clarity, and measurable business value. Key Responsibilities Discover client business processes, pain points, and opportunities where AI and automation can deliver value. Elicit and document requirements for AI/ML‑powered solutions, including model inputs/outputs, training data needs, and business rules. Define and document AI use cases, including LLM integrations, predictive analytics, intelligent automation, and conversational AI workflows. Map data flows between AI models, consumers, and providers across integrated systems. Create and manage JIRA tickets with acceptance criteria, implementation details, AI model behaviour expectations and edge cases, and consumer/provider mappings. Document solution artefacts in Confluence, including UML sequence diagrams for AI‑integrated workflows, integration design patterns (AI APIs, model endpoints, orchestration layers), prompt engineering guidelines and LLM behaviour specifications, mapping tables, endpoints, and environment configurations, Postman collections for AI API testing, and acceptance criteria for AI model outputs and responses. Facilitate workshops and discovery sessions focused on AI opportunity identification and solution scoping. Lead 3 Amigos sessions (Dev, Tester, BA) emphasizing AI model validation, bias considerations, and responsible AI outcomes. Collaborate with Data Scientists and ML Engineers to translate business requirements into model specifications. Champion responsible AI principles, ensuring ethical considerations, explainability, and compliance are embedded into solution design. Define data model requirements to support AI/ML training pipelines and inference outputs. Document HTTP operations, data types, and payload structures for AI model APIs. Design and maintain integration patterns connecting AI services to enterprise systems. Create Swagger/OpenAPI specifications for AI service contracts. Design error‑handling patterns for AI inference failures, model timeouts, and confidence threshold responses. Support event‑streaming architectures using Message Queuing technologies such as Kafka and ActiveMQ. Provide estimates for AI change requests and solution delivery, accounting for model iteration cycles and data preparation timelines. Lead client reviews of draft design documents and obtain sign‑off. Contribute to AI solution roadmaps, identifying phased delivery approaches aligned to business priorities. Work with Technical Leads, Architects, and Data Scientists to ensure functional requirements are understood for AI system architecture design. Collaborate with Test Analysts to define AI‑specific testing strategies, including model validation, A/B testing, and output quality benchmarks. Resolve ambiguities raised by developers and testers in relation to AI model specifications. Monitor and communicate scope changes, AI‑related risks, and project issues to Technical Leads and stakeholders proactively. Provide the team with AI industry best practices, emerging trends, and governance advice. Support user guides and AI usage documentation to aid end‑user adoption of AI‑powered solutions. Ensure design and compliance reviews are completed at required checkpoints, including responsible AI assessments. Tools & Experience Project & Documentation: Confluence, JIRA. API Design & Testing: Swagger/OpenAPI, Postman, SOAP UI. AI Platforms: Azure OpenAI, AWS Bedrock, Vertex AI, Hugging Face. Data & Monitoring: Splunk, Power BI. Development Environments: IntelliJ, Eclipse, VS Code. Source Control: Git, Bitbucket. Messaging & Streaming: Kafka, ActiveMQ. AI/ML Tooling: LangChain, Prompt Flow, Jupyter Notebooks (awareness). Qualifications & Professional Qualities 5+ years of experience as a Technical Business Analyst, with demonstrable exposure to AI, ML or data‑driven solutions. Strong analytical mindset with the ability to critically evaluate AI model outputs and business implications. Exceptional attention to detail, particularly when documenting complex AI workflows and edge cases. Deadline‑driven with the ability to manage competing priorities in a fast‑paced AI delivery environment. Excellent communication skills – able to translate complex AI concepts for both technical and non‑technical stakeholders. Collaborative team player with experience working in cross‑functional Agile teams. A natural curiosity and passion for emerging AI technologies and their practical business applications. #J-18808-Ljbffr