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AI Summary
Director, Strategic Projects AI
Solovis is a leading portfolio management and analytics platform helping institutional investors navigate today’s complex global markets with clarity and confidence. Backed by Insight Partners, were building the next chapter of growth by investing in people and product to raise the bar on quality and client outcomes. Our team is driven by a culture of disciplined execution, humility, and curiosity where AI is at the core of how we operate, innovate, and serve clients. At Solovis, you'll join a tech-forward, growth-minded team that believes in learning fast, thinking big, and delivering meaningful impact for asset owners worldwide.
The Director, Strategic Projects AI owns the end-to-end delivery of high-priority AI initiatives across Solovis. This individual leads autonomously, drives AI adoption across the organization, and ensures data-driven decision making is embedded in how we build and deliver for clients.
Key Responsibilities
- Lead autonomous delivery of strategic AI projects from inception through completion, owning scope, timeline, and outcomes
- Drive AI adoption and evangelism internally, helping teams integrate AI tooling into daily workflows and product decisions
- Coordinate cross-functional stakeholders across product, engineering, sales, and client success to align commitments and resources
- Apply quantitative and qualitative data to inform project direction and measure success
- Partner with leadership to evaluate and prioritize the AI project portfolio against business objectives
Key Qualities
- Operates with a high degree of autonomy and drives initiatives to completion without close oversight
- Proactive problem solver who anticipates obstacles and resolves them before they affect delivery
- Decisive under ambiguity, with a habit of grounding recommendations in data
- Communicates with clarity and concision, adapting to technical and non-technical audiences
Skills
- Demonstrated experience managing complex, cross-functional projects in a technology or SaaS environment
- Proficiency in data analysis and reporting, with the ability to translate findings into actionable recommendations
- Working knowledge of AI tools, frameworks, and adoption patterns in a business context
- Technical acumen sufficient to engage credibly with engineering and product teams
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