Chief Architect & VP of AI at Sprouts.ai
PhD in Artificial Intelligence
Dr. Junaid Farooq is Chief Architect and Vice President of AI at Sprouts.ai, where he leads the engineering and AI organisation behind its AI-native go-to-market platform. Working closely with the CEO and executive team, he sets the technology strategy and platform architecture for products that automate marketing and sales and turn business data and buying signals into actionable intelligence.
He architected and launched Sprouts Data (sproutsdata.ai), a business-data API and MCP server that gives AI agents, developers and enterprises access to company, people, patent and research data. He also led the technical side of the company’s $9M pre-Series A and of its acquisition of StartUs Insights’ technology and AI IP, from investor discussions to due diligence and negotiations.
Previously Head of AI at StartUs Insights in Vienna, an innovation-intelligence platform serving more than 1,000 corporate partners, he has led both companies’ transformation from traditional SaaS to AI-native products.
He holds a PhD in Artificial Intelligence from the National Institute of Technology Srinagar, where his research addressed a central weakness of deep learning models: the errors that compound as they predict further ahead. He has published multiple peer-reviewed papers and is the author of two books, ZERO DAY: The Invisible War and The Art of Code.
Two companies taken from legacy SaaS to AI-native products.
Chief Architect & VP of AI
Leads the engineering and AI organisation behind Sprouts.ai’s AI-native go-to-market platform, owning technology strategy, platform architecture and the product roadmap in close partnership with the CEO, CTO and CRO. Architected and launched Sprouts Data, a business-data API and MCP server for AI agents, developers and enterprises.
Principal ML Architect & Head of AI · Vienna, Austria
Led the platform’s shift from big-data SaaS to AI-native products: a multi-agent AI platform and a semantic search engine over innovation data, used by more than 1,000 corporate partners.
Machine Learning Engineer & Head of R&D · Toronto, Canada
Led research and development for conversational AI systems built on large language models.
My research on deep learning and AI retrieval, explained in depth.
Semantic Compression Trees: Multi-resolution knowledge retrieval via hierarchical semantic residuals
arXiv, 2026
RefreshNet: Learning multiscale dynamics through hierarchical refreshing
Nonlinear Dynamics, 2024
Deep learning for self-tuning of control systems
ICETCI 2021, IEEE, 2021 · Best Paper Award
Essays on how AI teams work and what slows them down.
On AI security, and on building software that lasts.
Leadership roles, advisory work, interviews and talks.
