• Building the ML foundation for Cloudflare’s new Security Intelligence and Detections (SID) team to unify how we catch threats across the entire platform.

• Turning Cloudflare’s massive data advantage into real-time detection signals by researching and deploying new ML models at scale.

• Leveraging LLMs and generative AI to automate the triage of security signals cutting down false-positive rates and speeding up how we fix false negatives.

• Scaling detection engines for AV, sandboxing, and automated threat feeds to improve security across Gateway, DLP, and Email products.

• Owning detection efficacy with a focus on cutting down false positives and speeding up how quickly we fix false negatives through automated workflows.

• Shipping research into production by partnering with Cloudforce One to turn high-level threat intel into active defense models.

• Creating a "single source of truth" for intelligence so every product team can plug into a centralized detection engine.

Building the future of AI and security

• Achieved 100% year-over-year growth for the email security product line while overseeing the integration of the Area 1 Security acquisition into Cloudflare's Zero Trust platform.

• Led product strategies that positioned Cloudflare as a Leader in The Forrester Wave: Enterprise Email Security, 2023, and got the 3rd highest product capability score in the 2025 evaluation, with a strong emphasis on AI-driven detections that differentiated our offering

• Spearheaded the integration of email security with Zero Trust architecture resulting in increased enterprise adoption.

• Launched native API scanning capabilities which is now utilized by multiple Fortune 500 enterprises, alongside DLP integrations employing machine learning to prevent data exfiltration.

• Collaborated with machine learning teams to define essential models and efficacy standards, leading to the creation of Cloudflare's Defensive AI framework. This initiative developed advanced AI-driven detections for phishing, generative AI threats, etc. and featured in investor communications.

• Designed integrations with CrowdStrike and other vendors while expanding market presence by introducing Cloudflare's email security solution to cloud marketplaces to drive revenue.

• Authored product requirements documents (PRDs) and vision statements to unify cross-functional teams on AI priorities. Helped in the launch of innovative features and expanding our use of LLM's within the business.

• Established a program providing free AI-powered email security to political campaigns, safeguarding over 100 campaigns during the 2022 midterm elections by blocking more than 150,000 phishing attempts.

• Dedicated extensive efforts to AI-centric initiatives, including model design for advanced threat detection and the integration of generative AI defenses.

Acquired by Proofpoint

• Tessian is a Cloud Email Security solution that uses AI to help detect different anomalies like phishing and data loss within a company’s email ecosystem

• Performed primary and secondary market research to create a cohesive argument on why Tessian should pursue building a new product to catch internal account takeovers (iATO). Created several documents for the leadership team which highlighted how iATO was going to help achieve the revenue goals highlighted by our board.

• Led customer interviews to define what threat signals needed to be included in the MVP in order for customers to buy the product. Defined user stories and worked with data science to help guide the development of the algorithms.

• Managed the beta program for the iATO module and created a strong feedback loop that improved the algorithm at a faster pace. Created the proper SLAs to ensure that the new product’s false positive rate/latency/etc. were within acceptable limits for launch.

• Responsible for leading external integrations with partners in the cybersecurity ecosystem like SIEM/SOARs as well as EDRs

• Led customer interviews to establish the need for deeper operational metrics. Built out requirements for revamping our product to collect these metrics as well as provide it in a report which customers could run on demand. Oversaw the full development from ideation to launch as well as post-launch adoption/marketing

• Maintained AI detection portfolio. Created requirements for new detections and worked with Data Scientists to ensure the model's output was in line with what customers were expecting.

• Communicated with customers in the pre-sales/POV process about the product roadmap and what value the Vectra Platform provides.

• Identified a $2.1B gap within the healthcare market that led to over 108M Americans not seeing a dentist for their oral health needs and created a solution that used AI and computer vision to help decrease this disparity. Raised venture capital money and scaled a team from 3 to 12 to help accomplish this goal.

• Conducted customer interviews with clinicians globally to discover our platform’s value proposition and wrote corresponding copy to improve our positioning with customers. This increased our sales conversion rate by a factor of 2 and increased the organic searches for our product.

• Led a multi-person team to create an AWS/Firebase/Flutter enabled mobile app, over the course of 4 product sprints. Managed the creation of user stories and collected metrics after each sprint to measure the success of each feature set and communicated these to relevant stakeholders to help change the product roadmap.

• Translated insights from published AI algorithms using Pytorch and Transfer learning to detect the presence of periodontal diseases earlier which increased accuracy from 73% to 86% while decreasing the false positive rate

• Conducted competitor analysis and market analysis to ensure that our platform was staying competitive and innovating at a fast rate which led to winning first place at the biggest AI in medicine conference in America

• Accepted into HAX accelerator, most competitive hardware accelerator (under 2% acceptance), where we applied the IDEO product design method to discover user needs and iterate them into our product.