Solution Development Consultant, Workiva

• Success in this role requires comfort with ambiguity, a strong grasp of data and AI applications, and the ability to move ideas from concept to implementation through practical, actionable approaches
• Undergraduate degree or equivalent combination of education and experience in a related field
• 5+ years of experience in product management, solution architecture, technical consulting, or SaaS pre-sales
• 20% travel for customer and internal meetings
• Reliable internet access for any period of time working remotely and not in a Workiva office

Desirable

• As a Solution Development Consultant (SDC) within Workiva’s Growth Organization, you’ll play a pivotal role in identifying and shaping the company’s next generation of solutions aimed at simplifying complex work
• This role focuses on early-stage solution discovery, requiring a unique blend of customer insight, technical problem-solving, and strategic thinking to turn loosely defined opportunities into validated SaaS concepts
• This position emphasizes solution incubation and innovation
• You’ll explore new markets, collaborate cross-functionally to develop prototypes, and rigorously evaluate emerging ideas
• Lead customer interviews, workshops, and data analysis to uncover unmet needs
• Synthesize findings into clear problem statements and opportunity briefs
• Evaluate opportunities through the lenses of customer value, business value, and technical feasibility
• Draft end-to-end solution blueprints, including workflows, data models, and security requirements, while partnering with engineering to align technical direction with customer needs
• Define MVP scope, success criteria, and test plans collaboratively with engineering and design
• Build low- and high-fidelity prototypes or proofs of concept to visualize and validate key ideas
• Define product requirements and use cases for AI-powered features, particularly in regulated and data-sensitive environments
• Translate business and user intent into functional models for AI agents, copilots, and decision-support tools
• Document assumptions, guardrails, and evaluation metrics to ensure responsible and effective AI integration
• Serve as the technical liaison in customer conversations, clearly communicating engineering constraints without needing real-time support from technical teams
• Partner with Product, Design, and Marketing to stress-test solution concepts through pilots and iterative experiments
• Drive continuous iteration based on results, refining both the problem framing and solution architecture
• Capture and share learnings, pivot recommendations, and rationale to inform future Product and GTM strategies
• Establish KPIs and success metrics for validation-stage experiments and MVP initiatives
• Lead retrospective reviews to extract actionable insights from both successful and unsuccessful efforts
• Inform long-term roadmap development for emerging solution investments