Technical Business Analyst - AI at Datacom

Wellington, Wellington, New Zealand -

Full Time

Start Date

Immediate

Expiry Date

29 Jul, 26

Salary

0.0

Posted On

30 Apr, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Technical Business Analysis, Artificial Intelligence, Machine Learning, API Design, Swagger, OpenAPI, Postman, JIRA, Confluence, Data Modeling, Prompt Engineering, LLM, Integration Patterns, Agile, Requirement Elicitation, System Documentation

Industry

IT Services and IT Consulting

Description

Our purpose Here at Datacom, we connect people and technology in order to solve challenges, create opportunities and discover new possibilities for the communities we live in. About the Role As technology evolves at an unprecedented pace, Datacom is looking for a Technical Business Analyst with a strong AI focus to bridge the gap between cutting-edge AI capabilities and real-world business outcomes. You will play a pivotal role in shaping AI-driven solutions, ensuring intelligent systems are designed, documented, and delivered with precision, clarity, and measurable business value. What You'll DoRequirements Discovery & AI Solution Design Understand the client's 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 Documentation & Artefact Creation Create and manage JIRA tickets including: Acceptance criteria Implementation details AI model behaviour expectations and edge cases Consumer/provider mappings Document all 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 Acceptance criteria for AI model outputs and responses AI-Focused Facilitation & Collaboration Facilitate workshops and discovery sessions focused on AI opportunity identification and solution scoping Lead 3 Amigos sessions (Dev, Tester, and BA) with an emphasis on 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 Data & Integration 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 Technical AbilityAPI & Integration Skills Create Swagger/OpenAPI Specifications for AI service contracts — using Swagger Editor, VS Code, or equivalent Deep understanding of integration patterns: REST APIs, SOAP, event-driven architectures API contract design and maintenance for AI model endpoints (e.g., OpenAI, Azure AI, AWS Bedrock, custom ML APIs) Error handling patterns for AI inference failures, model timeouts, and confidence threshold responses Experience with Message Queuing technologies such as Kafka and ActiveMQ for AI pipeline event streaming AI & Machine Learning Awareness Working knowledge of LLMs (Large Language Models) — including prompt engineering, RAG (Retrieval Augmented Generation), and fine-tuning concepts Ability to document AI model behaviour requirements including confidence scoring, hallucination mitigation strategies, and output validation Understanding of AI/ML pipeline stages: data ingestion, preprocessing, model training, deployment, and monitoring Familiarity with AI platforms and services such as: Azure OpenAI / Azure AI Studio AWS SageMaker / Bedrock Google Vertex AI Hugging Face Awareness of AI governance frameworks, including model explainability (XAI), fairness, and regulatory compliance (e.g., EU AI Act) Estimation & Delivery Provide reliable and traceable estimates for AI change requests and solution delivery, accounting for model iteration cycles and data preparation timelines Design systems from a functional AI perspective, producing draft Design documents and leading client reviews through to sign-off Contribute to AI solution roadmaps, identifying phased delivery approaches aligned to business priorities Responsibilities As a Technical Business Analyst (AI Focus), your day-to-day activities will include: Produce drafts of Requirements and Design documents for AI-integrated solutions, lead client reviews, and achieve sign-off Lead the Analysis and Design stage for AI initiatives, arranging and facilitating all relevant workshops and communication Work closely with Technical Leads, Architects, and Data Scientists, ensuring they have sufficient understanding of functional requirements to design AI system architecture 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, communicating with clients as required 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 Contribute to User Guides and AI usage documentation, supporting end-user adoption of AI-powered solutions Ensure all 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 CodeSource ControlGit, Bitbucket Messaging & Streaming - Kafka, ActiveMQ AI/ML Tooling - LangChain, Prompt Flow, Jupyter Notebooks (awareness) 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 About Datacom With over 6,200 people across our global offices and an annual revenue exceeding $1.2 billion, Datacom is one of Australasia's largest professional IT services companies. We have deep expertise in data centres, IT services, software engineering, application management, and AI-enabled solutions. As AI reshapes industries, Datacom is at the forefront — partnering with clients to design and deliver intelligent, responsible, and impactful AI solutions. We are committed to hiring, developing, and promoting the best talent from diverse backgrounds. We are local at heart, yet world-class in capability.

Responsibilities

The Technical Business Analyst will bridge the gap between AI capabilities and business outcomes by designing, documenting, and delivering intelligent solutions. They will facilitate discovery workshops, collaborate with data scientists, and ensure AI systems meet functional requirements and ethical standards.