Technical Product Marketing Manager
Vega Ventures
Technical Product Marketing Manager
- Marketing
- US
- Full-time
Description
Vega is one of the fastest-growing startups in cybersecurity, redefining security analytics and operations with an AI-native platform for the SOC. We are building the next-generation operating system for security teams. Vega is already delivering real impact at some of the world’s largest organizations - improving detection, unlocking the value of their security data, and reducing cost and complexity. With HQs in New York and TLV, we’re looking for people who want to be a part of the next rocket-ship in cyber.
We’re hiring a Technical Product Marketing Manager with strong technical depth and field awareness. This is a hands-on, practitioner-focused role at the intersection of product, sales, and customer engagement. You should be comfortable going deep on technical topics, building narratives from real-world experience, and treating competitive intelligence as a core function.
WHAT YOU WILL DO
Technical Storytelling & Messaging
- Develop clear, differentiated messaging for technically complex cybersecurity products.
- Craft demo narratives tied to real attack scenarios, SecOps workflows, and measurable outcomes - not just feature walkthroughs.
- Write from both a practitioner and marketing perspective, with credibility across Detection Engineers, SOC Analysts, Data Engineers, and Security Architects.
Field & Customer Engagement
- Act as a trusted technical voice with customers and prospects - including architecture discussions and data infrastructure.
- Partner closely with Sales and Solution Engineering, and at times lead technical conversations.
- Represent Vega at conferences, partner events, and field engagements. Some Travel required.
Competitive Intelligence
- Build technical competitive analysis across product capabilities, architecture tradeoffs, detection coverage, and cost.
- Run win/loss analysis and maintain live competitive tracking (battlecards, Gong insights, field feedback).
- Treat competitive intelligence as an ongoing, operational function.
Sales & SE Enablement
- Support enablement through training, pitch decks, objection handling, and demo playbooks.
- Translate complex product capabilities into assets that help Sales and SEs win and expand deals.
- Continuously refine materials based on field feedback and performance data.
Technical Alliances & Partner GTM
- Develop integration narratives and “better together” stories with technology partners.
- Support partner enablement, channel GTM, and co-marketing from concept through execution.
Product Domain GTM & Launches
- Contribute to GTM across Vega’s core product areas (Analytics, Detection, Triage, Integrations)
- Support launches as a way to drive pipeline and shape market perception.
- Create technical content (blogs, solution briefs, whitepapers, webinars) with both depth and clarity.
Requirements
WHAT YOU WILL BRING
Technical Fluency
- 4+ years of experience in a relevant cybersecurity company
- Understanding of query languages (especially KQL) and how AI can bridge across systems.
- Familiarity with AWS, Azure, GCP, and object storage (S3, ADLS, GCS).
- Exposure to security data infrastructure (pipelines, data lakes, normalization, detection content) is a plus.
SecOps Domain Expertise
- Understanding of SOC workflows across detection engineering, data engineering, and security architecture.
- Familiarity with SIEM, XDR, SOAR, EDR, and modern data lake architectures.
- Experience with or against vendors like Splunk, CrowdStrike, Panther, Chronicl Elastic, etc.
Storytelling from Experience
- Ability to build narratives grounded in real-world experience, not templates.
- Comfort communicating with both technical practitioners and executives without losing credibility.
Execution & Launch Experience
- Experience supporting successful product or feature launches in B2B cybersecurity.
- Demonstrated impact on sales through messaging, enablement, and demos.
- Comfort operating in a fast-paced, high-growth environment.
AI Fluency
- Experience using AI tools (e.g., Claude, Claude Code) as part of daily workflows across research, writing, and analysis.