Engineering Manager, Workiva

• Bachelor’s degree in a related field with 5+ years of relevant engineering experience, or equivalent experience in lieu of a degree
• 3+ years directly managing engineers, including supervisory experience of supervisors and/or individual contributors

Desirable

• You will build and lead the engineering team behind GRC Reporting, a new domain that unifies how reporting works across all of Workiva’s GRC solutions
• Today, GRC reporting is fragmented. Practitioners pull data from one system, build charts in another, and write narrative in a third. This team exists to change that: one composition layer, one set of principles, one owner accountable for how it all connects
• This role is accountable for the health of a delivery pipeline, the growth of the engineers on it, and the quality bar the team holds itself to. You will own the engineering decisions, architecture, and resourcing for a domain where AI-native reporting is the north star
• Reports will be generated from actual findings, and where every output must be structured, traceable, and trustworthy enough for boards, auditors, and regulators
• Lead a team of engineers, assigning roles and tasks based on team goals and individual growth areas
• Own the delivery schedule for your team and communicate risk to group leadership early
• Own the reporting system, principles, and patterns that govern how reporting looks, behaves, and connects across all GRC solutions
• Drive development of the composition layer: charts, narrative, tables, dynamic data, template import, and report generation
• Build and maintain lineage, versioning, and persistence infrastructure that makes outputs trustworthy and defensible
• Define and execute product quality strategy in partnership with group leaders and individual contributors
• Reinforce Workiva values, principles, product development standards, and agile practices across your squad(s)
• Assess and document individual performance accurately, recognizing real contribution and growth, not just output volume
• Run regular 1:1s that build trust and surface what’s actually going on, not just status updates
• Coach engineers through career development, technical growth, and obstacles, including hard conversations when performance needs to change
• Own team health: build a positive, engaged environment and resolve conflict directly rather than letting it fester
• Prioritize your reports’ growth deliberately, identifying and creating opportunities that match where they want to go
• Participate actively in recruiting, selection, and onboarding of new team members
• Serve as the engineering voice in the GRC Reporting triad alongside the Product Manager and UX Lead, shaping domain direction together
• Manage collaboration at the “seam” where outcome teams (controls management, audit management, risk management) hand off data and workflow into the reporting experience; define handoffs clearly and early
• Define how GRC data needs to be structured to be reportable, and hold outcome teams accountable for meeting those requirements
• Represent your team’s resourcing needs and priorities to group leadership with clear tradeoffs, not just requests
• Partner with group leaders to define and plan team and group objectives
• Identify technical risk early and communicate it clearly to leadership, before it becomes a fire
• Build toward AI-native reporting workflows where reports are generated from actual GRC data and refined through natural language while maintaining full manual paths for practitioners who need them
• Ensure all AI-generated outputs are explainable, auditable, and traceable to source data. (AI capabilities that cannot be explained or traced back have no place in GRC Reporting)
• Hold the quality bar for AI-generated content to the trust standard required by high-stakes GRC audiences: boards, audit committees, and regulators
• Evaluate your team’s output based on judgment and outcomes, not shipped volume, distinguishing genuine skill growth from AI-assisted output that looks productive but isn’t
• Ensure your team’s code review and quality gates keep pace with AI-generated code, catching hallucinated logic, subtle errors, and security gaps before they ship
• Coach engineers to work effectively with AI while keeping the ability to work and reason without it