Loading profile…
Loading profile…
Eric La Rosa — Vice President · Mantle · San Francisco Bay Area.
Direct contact
No direct contact on file for Eric yet.
About
As an accomplished leader in enterprise sales and sales engineering, I bring over 15 years of experience driving growth and achieving quota in the technology sector. My career has been defined by a strategic focus on artificial intelligence, cloud-native platforms, and modern agile development methodologies.
I've played a pivotal role in leading three high-impact startups—BEA Systems, Pivotal, and C3.ai—through major exits, including IPOs and acquisitions valued at over $5 billion. My expertise lies in developing and scaling repeatable sales processes, crafting compelling value propositions for digital transformation, and driving substantial deals worth $4M to $10M+ with C-suite engagement.
Currently, I am the founder of an innovative AI platform for algorithmic trading. My hands-on approach has led to the design and development of advanced data infrastructures and predictive models that have delivered impressive returns. I continue to push boundaries by researching LLM Transformer architecture for multivariate time series analysis.
My track record includes exceeding sales quotas, securing major clients, and developing strategic marketing collateral across various roles—from Vice President of Sales at C3.ai to Sales Director at Pivotal. With a deep understanding of product management, consulting, and sales strategy, I am passionate about driving transformation and achieving excellence in every endeavor.
Experience
Vice PresidentCurrent
Mantle · San Francisco Bay Area
Mar 2025 – Present
Driving broad adoption of a platform for managing private assets | At the forefront of multimodal foundation models and agentic reasoning systems
Founder
Jun 2020 – Present
Designed, developed, tested and operated an AI Platform for Stock Price Prediction and Algorithmic Trading. Employs streaming data persisted throughout the trading day, with metrics calculated commonly utilized in technical analysis, including pattern identification. Predicts stock prices hours in advance and uses those to generate buy and sell signals throughout the trading day, every 30 minutes. A full quarter trading test on a volatile tech stock yielded almost 18% gains despite the underlying stock having dropped over 50% and the Nasdaq dropping 10% in the same period. Runs on AWS SageMaker, current version employs XGBoost for random forests which are trained nightly for use the next trading day. Self funded. See article on this profile for more details.
Education
Skills
Related professionals · Mantle