# Greg Nudelman

> Sr. Director, AI Product (Cybersecurity) | Built Agentic SOC Systems for SIEM & Threat Detection | Sumo Logic, LogicMonitor, Cisco, GE

Location: San Francisco Bay Area, United States
Profile: https://flows.cv/gregnudelman

OpenClaw Agentic AI attacks are here. SOC teams need autonomous Agentic AI to complete investigations before an analyst even opens the alert, and defensive systems that block attacks before they happen. At machine speed.

I build and scale those Agentic AI cybersecurity and observability systems.
  
At Sumo Logic (cloud-native SIEM serving Fortune 500 SOC teams, direct Spulnk competitor), I owned the AI product portfolio direction and delivery across agentic SOC initiatives, aligning engineering, data, and GTM teams around production deployment:
 
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 at AWS re:Invent
 → Deployed in production SOC workflows across enterprise environments 

Led 0→1 development of Mo Copilot, translating natural language into SIEM queries using RAG-based semantic search at enterprise scale.

Led delivery of production-grade RAG and Agentic AI MCP infrastructure:
 → Improved accuracy to 98%+
 → Reduced hallucinations from 40% to under 2% 
 → Introduced AI safety architecture (“Judge”) into production systems
 → Now, judge-in-the-loop runs on every autonomous AI decision.
 
I’ve spent 10+ years building AI systems for security and observability:
  → SIEM, threat detection, and investigation workflows 
  → Agentic and conversational AI systems (pre- and post-LLM era) 
  → Real-world SOC environments with Fortune 500 teams 
 
From early systems at Cisco to modern agentic architectures at Sumo Logic, my focus has been the same: turning complex security workflows into systems that operate on real data and deliver measurable outcomes.
 
 Led AI product M&A evaluation and integration at LogicMonitor:
 → Contributed to growth from $50M to $200M ARR 
 → Built and scaled cross-functional teams (2 → 14 across 4 countries) 
 
I’m focused on owning and scaling AI-driven cybersecurity products—especially SOC, SIEM, and threat detection systems operating on real data in production environments.

## Work Experience
### Senior Director of AI Product Management @ Hackerdogs
Jan 2025 – Present | San Francisco Bay Area
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.

### AI Product Lead, Cybersecurity (SOC, SIEM, Agentic Systems) @ Sumo Logic
Jan 2022 – Jan 2025 | Redwood City, CA
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.

### Sr Director, AI Product (Observability & AIOps) @ LogicMonitor
Jan 2019 – Jan 2022 | Pleasanton, CA
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.

### Founding AI Product Lead | Sr. Director (AutoML Platform) @ Aible
Jan 2018 – Jan 2019 | San Mateo, CA
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).

### AI & IoT Innovation Lead | Sr. Director @ GE Digital
Jan 2017 – Jan 2018 | San Francisco Bay Area
→ 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.

### AI Product Lead & Head of UX @ Cisco
Jan 2016 – Jan 2017 | San Francisco Bay Area
→  Designed strategic workflows that validated Cisco's $3.7B AppDynamics acquisition. 
→  Led UX strategy for a $20M, 45-person internal observability platform.
→ Personally built 2 pre-ChatGPT conversational AI products (2016): Security rule creation copilot (Microsoft Bot Framework + LUIS) and Slack-based investigation assistant — natural language queries against security data.

### Adjunct Professor, AI & Design @ Marquette University
Jan 2009 – Jan 2016 | United States
Created Snowball Sprint Instructor-Led LinkedIn Learning Course teaching AI-first cross-functional team collaboration and rapid iteration with real AI-driven prototypes and RAG. (2025)

Taught AI-driven design, data visualization, and human-AI interaction at graduate and undergraduate level at Marquette University, San Francisco State, Hult International—years before AI became mainstream curriculum.

Pioneered coursework integrating ML concepts into design education, preparing students to build intelligent systems alongside data scientists.

Created O'Reilly Media video course on product design methods.


## Education
### Master of Science - MS in Computer and Information Sciences and Support Services
Golden Gate University

### Bachelor of Science - BS in Biochemistry
San Francisco State University


## Contact & Social
- LinkedIn: https://www.linkedin.com/in/gregnudelman
- Website: http://www.SnowballSprint.com

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Source: https://flows.cv/gregnudelman
JSON Resume: https://flows.cv/gregnudelman/resume.json
Last updated: 2026-04-07