Reporting to the Head of Data & AI and leading a small team of specialists, the role owns three things: Azure-based AI/BI and agentic offerings; Mivada's Responsible AI, data governance and AI assurance framework; and the Microsoft Data & AI partnership.

This role works alongside the Enterprise Architecture & Snowflake COE, the Solutioning & Databricks COE, Pre-Sales, Propositions & Industry Engagement, and Client Engagement & Execution, and drives the governance, training and adoption program set out in Mivada's AI Strategy & Roll-Out Roadmap across the practice.

Team leadership and people management

- Lead and manage a team of 3-5 Azure AI/BI engineers and AI / data governance specialists, owning their performance, development and day-to-day workload allocation.
- Recruit, onboard and develop team members; act as the escalation point for technical, governance and client issues the team raises.
- Set goals and conduct regular performance reviews for direct reports; identify and act on development and career-progression needs.

Azure AI/BI and agentic solution design and delivery

- Design, build and productionise AI/BI and generative AI solutions on Microsoft Azure, Microsoft Fabric and Microsoft Foundry, including natural-language analytics (for example, Fabric data agents and Copilot in Power BI).
- Develop and orchestrate agentic AI workflows (for example, Foundry Agent Service, Copilot Studio or LangGraph-style supervisor/agent patterns) that connect governed enterprise data, models and knowledge sources to real business problems.
- Package proven patterns into named, reusable, sellable offerings with the Pre-Sales, Propositions & Industry Engagement lead,



contributing to the practice's goal of at least one client-facing AI-enabled capability.
- Hand over to Client Engagement delivery pods with clear designs, guardrails and runbooks, and provide technical assurance through delivery.

Data governance and trust

- Own the practice's data governance approach for AI and analytics: ownership and stewardship, classification, lineage, quality and cataloguing, using Microsoft Purview and, where relevant, Unity Catalog or Snowflake Horizon.
- Develop and deliver client-facing trust offerings such as AI governance operating models, data governance and AI-readiness assessments, and Copilot data-protection reviews.

Microsoft Data & AI partnership

- Own Mivada's Microsoft Data & AI partner relationship and partner-tier roadmap, including the Solutions Partner for Data & AI (Azure) designation and relevant specialisations.
- Lead Microsoft co-sell, joint go-to-market and partner-funded programs (for example, workshops, assessments and proofs of concept) together with the Pre-Sales, Propositions & Industry Engagement lead.
- Build and maintain certified Microsoft Data & AI capability across the practice, including own hands-on delivery.
- Represent Mivada at Microsoft partner forums and build relationships with Microsoft partner development managers and solution specialists.

Internal AI enablement and capability uplift





- Build and maintain the reusable prompt/playbook library and templated workflows that move staff from ad hoc use (L1/L2) toward governed, team-level and client-facing use (L3+) on the practice's AI maturity scale.
- Recruit, train and coordinate the peer-coach network; deliver the role-based training tiers, including Responsible AI and AI literacy for all staff; track adoption, confidence and training completion each quarter.

Client and stakeholder engagement

- Partner with the Pre-Sales, Propositions & Industry Engagement lead on AI and governance pursuits, providing solution design, estimates and Responsible AI positions for proposals.
- Contribute Responsible AI and data-trust thought leadership, such as points of view, events and case studies, to build Mivada's reputation and visibility.
- Advise client executives and risk, privacy and compliance stakeholders on AI governance, guardrails and trade-offs in explicit, non-technical terms.
- Keep current with the Azure, Fabric and Foundry roadmap and with AI regulation and standards; coach consultants in Azure AI delivery and Responsible AI practice.

Essential

- Demonstrated experience leading and developing a small technical team (line management, performance reviews, resourcing and capacity planning).
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science or a related discipline, or equivalent practical experience.
- Senior experience in data and AI engineering or consulting, with hands-on delivery on Microsoft Azure data and AI services (for example, Microsoft Fabric, Foundry, Azure OpenAI and Power BI).
- Practical experience building and productionising generative AI, natura

📌 Data & AI Architect (Sydney)
🏢 Mivada
📍 Sydney