Engineering Lead

Overview

A product-minded Power Platform and AI engineering leader who is accountable for outcomes and able to balance hands-on delivery with leading a workload across multiple initiatives. Comfortable taking ambiguous business requirements, running structured discovery, and turning them into clear user stories, acceptance criteria, solution designs, and a prioritised delivery backlog.

Skilled at influencing across business and technology, setting pragmatic standards (Power Platform governance, security, DLP, environment strategy, ALM with GitHub and pipelines) while enabling maker autonomy through templates, coaching, and guardrails. Communicates clearly with technical and non-technical stakeholders, and translates risk, compliance, and operational considerations into practical actions and priorities.

Responsibilities

Product Intake, Delivery & Automation

• Establish a clear intake-to-delivery process: discovery, user stories, acceptance criteria, prioritised backlog, and release plans for Power Platform and Copilot initiatives
• Create and maintain templates and reusable components for common patterns (Power Apps, Power Automate, Dataverse, connectors, approvals, notifications, integrations) to reduce cycle time and improve consistency
• Measure and improve flow and outcomes using lead time, deployment frequency, defect/rework rate, adoption/usage, and automation savings with transparent reporting to stakeholders

Operational Ownership, Monitoring & Support

• Define service levels for business-critical apps/flows/bots and implement monitoring, alerting, dashboards, and runbooks (including flow failures, connector issues, and capacity signals)
• Run effective incident triage and support processes with clear ownership, escalation paths, and blameless reviews to reduce repeat failures and improve reliability
• Improve resilience through environment strategy, controlled releases, automated testing where appropriate, and documented recovery steps (including rollback and break-glass access)

Copilot / AI Solution Lifecycle

• Operationalise Copilot Studio and AI-enabled solution lifecycle practices: versioning, approvals, test plans, safe rollout/rollback, and change control aligned to governance
• Implement monitoring for response quality, grounding/data access, safety signals, latency, cost, and adoption; ensure clear ownership and escalation paths for issues
• Embed governance controls aligned to security, privacy, and compliance requirements (data handling, access controls, audit logs, retention) for all AI-assisted experiences

Tooling, ALM & Cost Management

• Own and standardise the Power Platform toolchain and ALM approach (solutions, pipelines, GitHub repos, environments), promoting code quality, review, and repeatable deployments
• Manage platform capacity and cost (licensing, Dataverse storage, premium connectors, Copilot/AI consumption) with transparent reporting and optimisation actions

Qualifications

• Proven experience leading delivery across Power Platform (Power Apps, Power Automate, Dataverse) in a product or enterprise environment, balancing hands-on build with leading a workload
• Strong understanding of Power Platform architecture, environment strategy, Dataverse design, connector/integration patterns, and performance considerations
• Demonstrable experience implementing Power Platform ALM (solutions, source control in GitHub, branching/code review, automated deployment pipelines, and environment promotion)
• Experience with Copilot Studio and/or integrating AI capabilities into business processes, with an understanding of responsible AI, data boundaries, and prompt/response quality management
• Strong stakeholder management and facilitation skills; able to run discovery workshops, translate needs into user stories and acceptance criteria, and manage priorities with transparency
• Desirable: Power Platform CoE/governance experience (DLP, environment strategy), security fundamentals, and experience managing licensing/capacity and enterprise-scale adoption