Own product direction and go-to-market for an agentic AI cybersecurity platform, defining core use cases, product architecture, and early customer adoption strategy.

→ Own end-to-end product strategy and execution for a fully agentic cybersecurity platform, aligning engineering, data, and GTM around production-ready use cases

→ Defined initial product wedge (“Attack Surface in 3 Clicks”), translating complex security workflows into a differentiated, high-signal customer entry point

→ Led product architecture and onboarding design, shaping how agentic systems operate across real security workflows and how customers activate value from day one

→ Drove go-to-market strategy, including positioning, messaging, pricing, and early partnership strategy for an AI-native security product

→ Partnered directly with founders and engineering leadership to prioritize roadmap decisions, validate product-market fit, and accelerate delivery of production capabilities.

Cloud-native SIEM and log analytics platform serving Fortune 500 SOC teams (direct Splunk competitor).

Owned and drove development of agentic AI products for SOC detection and investigation workflows, delivering production systems operating on real customer data.

Led development and production deployment of Mobot, a 4-agent autonomous investigation system operating across telemetry, alerts, and correlated events:

→ Reduced MTTR from 60 minutes to under 3 minutes

→ Reduced false positives by 90%

→ Featured on the big stage at AWS re:Invent 2025

→ Made Sumo AWS Top 100 AI ISV

→ Deployed across production SOC workflows in enterprise environments

Owned product direction and delivery of Mo Copilot, translating natural language into SIEM queries using RAG-based semantic search.

Led delivery of production-grade RAG infrastructure, enabling semantic reasoning across large-scale security datasets:

→ Developed the new router RAG architecture (Agentic AI MCP skills in prod)

→ Improved accuracy to 98%+

→ Reduced hallucinations from 40% to under 2%

Introduced AI safety architecture (“Judge”) across autonomous decision pipelines, enabling real-time validation of AI-generated actions in production.

Drove cross-functional execution across engineering, data, and product teams, maintaining product direction through multiple leadership transitions while advancing AI strategy for SOC workflows.

Conducted 100+ customer sessions with Fortune 500 SOC teams to validate workflows, prioritize roadmap, and ensure real-world deployment success.

Maintained product vision and delivery continuity through 3 leadership transitions.

Filed US Patent 2025/0103418 — Signal Filtering Tool for correlated event analysis across investigation pipelines.

Cloud observability platform (direct Datadog competitor), serving enterprise IT and security teams.

Owned AI product strategy and execution across observability and AIOps initiatives, driving product expansion through M&A and new AI capabilities.

Led AI product strategy and integration for 3 acquisitions, bringing ML-powered anomaly detection and AIOps capabilities into the core platform

→ Helped drive growth from $50M to $200M ARR through AI product expansion and M&A integration

Owned product direction for AI-driven observability capabilities, aligning engineering, data, and product teams around scalable detection and analytics workflows

Drove cross-functional execution across global teams, scaling product and design org from 2 → 14 across 4 countries supporting 400+ engineers

Conducted 600+ hours of customer research with enterprise IT and security teams, translating real-world workflows into product requirements and roadmap priorities

Positioned AI capabilities as a core platform differentiator, enabling expansion into enterprise accounts and strengthening competitive positioning vs Datadog.

Owned product direction and delivery for an AutoML platform, taking the product from concept to GA in 90 days and enabling direct enterprise sales at Gartner Summit.

Co-invented 6 patents and contributed to rapid company valuation growth ($100M+ within 3 months post-launch).

→ Resurrected dormant AI product. Generated $42M+ pipeline from a single conference. Led AI strategy for industrial IoT — predictive maintenance and anomaly detection for BP, Chevron, Shell.

→ 6 patents filed. Voice AI for Industrial IoT (2017) — Alexa-based equipment monitoring, years before conversational AI went mainstream.