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Jared Alessandroni
Executive CTO specializing in AI, cloud platforms, and scaling SaaS products
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About
NYC-based startup founder/CTO who sold products to Omnicom and Sprinklr, then built an AI-powered cultural insights engine inside Omnicom using AWS Lambda + ML to process ~1M items/day and reached ~$1MM ARR in year one. Former senior leader at Sprinklr managing 200+ people globally, delivering enterprise martech solutions with SLAs and high-reliability social data pipelines (Twitter firehose).
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Key Strengths
- Shipped zero-to-one AI insights MVP in ~2 months under tight budget/bureaucracy constraints
- Hands-on CTO leadership across product, architecture, and coding (regular contributions across all repos)
- Built scalable cultural-trends pipeline processing ~1M items/day using AWS Lambda + ML models
- Grew product to ~$1MM ARR within first year (AI insights engine at Omnicom)
- Led large distributed org (managed 200+ people across multiple offices) at Sprinklr
- Enterprise delivery accountability via SLAs and bespoke implementations for major brands (Avon, Ford, Twitter, Coke)
- Designed reliability redundancies for mission-critical data ingestion (secondary Twitter stream to validate primary)
- Strong instrumentation/PMF iteration using product analytics (Pendo, Google Analytics) and customer feedback
- Early team builder with deliberate QA/DevOps prioritization and strong engineering culture practices (code review, pair coding)
Reference Highlights
- Full ownership of product engineering and technical strategy
- Strong at translating ambiguous concepts into delivered technical solutions
- Effective in zero-to-one, ambiguous environments
- Pragmatic tradeoff decisions prioritizing speed, stability, and user value
- Shipped first production version of an AI-powered platform
- Built and aligned a small cross-functional team around customer feedback and business objectives
- Built modular, flexible, model-agnostic systems enabling rapid iteration
- Designed scalable architecture (microservices, horizontal scaling) while maintaining speed
- Proactively anticipated and addressed bottlenecks
- Cost-effective tooling choices without compromising quality
- Led data-driven iteration toward product-market fit with marketing partnership
- Improved retention by analyzing engagement data and driving UX/functionality changes
- Often delivered beyond initial remit
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