AI Product Intelligence Lead

Job Title: AI Product Intelligence Lead 

Location: Ra'anana Israel - Hybrid

#LI-Hybrid

DriveNets is a leader in disaggregated high-scale networking solutions for service providers and AI infrastructures. Founded in December 2015, DriveNets created a radical new way to build networks by adapting the architectural model of the cloud to telco-grade networking. This solution accelerates network deployment, improves the network's economic model, and radically simplifies network operations. With customers including Comcast, Orange, and KDDI - over 80% of AT&T's network traffic now runs through a disaggregated core powered by DriveNets software. DriveNets Network Cloud-AI solution, based on the same technology, was introduced to the market in 2023, providing the highest-performance Ethernet-based AI networking solution, and is already deployed by Hyperscalers, NeoClouds and Enterprises. Raising over $587 million in three funding rounds, DriveNets continues to deploy the most innovative network infrastructure and is looking for the most talented people to be part of this journey. 

 Role Overview

 DriveNets is seeking a highly skilled AI Product Intelligence Lead to modernize and elevate the Product Management function by building an AI-driven product knowledge platform. This role focuses on aggregating and unifying organizational data (engineering, product, competitive, customer) into a structured data lake, and developing an internal AI assistant that empowers the Product organization with real-time insights, competitive analysis, roadmap support, and decision-making acceleration.

This position sits at the intersection of AI, data engineering, product strategy, and organizational knowledge management. You will function as the "AI engine" behind DriveNets Product Management — turning scattered information into structured intelligence and building the tooling that allows PMs to think faster, act smarter, and execute at scale.

Key Responsibilities

1. Build the DriveNets Product Data Lake

• Ingest and normalize data from internal systems including:
• Git / GitHub / GitLab (code evolution, releases, components, architecture)
• Jira (epics, features, sprint data, backlog health, execution trends)
• Confluence (specs, design docs, product decisions, reviews)
• Connect and harvest relevant external data:
• Competitor websites and public documentation
• Analyst reports, industry standards, RFCs
• Media, blogs, financial/market data, community repos
• Establish pipelines for continuous ingestion, cleaning, tagging, and semantic indexing.
• Define and enforce taxonomies, metadata schemas, and embedding strategies for structured and unstructured product information.

2. Build an AI Assistant for the Product Management Function

• Design and maintain a secure, internal DriveNets PM chatbot capable of:
• Understanding DriveNets architecture, products, roadmaps, modules, and features
• Generating roadmap proposals based on business goals, competitive gaps, and engineering capacity
• Providing competitive analysis, feature comparisons, and market positioning
• Summarizing design docs, Jira epics, technical specs, PRDs, RFCs, and Confluence pages
• Acting as an AI peer/consultant for PMs: drafting PRDs, feature breakdowns, risks, GTM summaries, and opportunity reports
• Implement multi-source retrieval (RAG), long-context reasoning, and fine-tuning strategies where applicable.
• Collaborate with Engineering to ensure data security, access control, and compliance.

3. AI-Driven Product Intelligence & Competitive Strategy

• Automatically identify gaps vs. competitors and recommend differentiators.
• Use AI to synthesize market intelligence and propose strategic moves.
• Build dashboards for product, competitive, and risk insights.
• Create automated alerts for competitor releases, standards changes, and relevant industry updates.

4. Cross-Functional Collaboration

• Work closely with Product Managers, R&D, Architecture, CTO Office, Sales Engineering, and Leadership.
• Translate business goals into AI capabilities and intelligence-driven tooling.
• Train PMs on using AI tools effectively and integrate AI into their daily workflows.

Required Skills & Experience

 Technical Must-Haves

• Strong experience with AI/ML tools, LLMs, RAG systems, vector DBs, prompt engineering.
• Practical experience with data engineering / data pipelines, including:
• ETL/ELT, ingestion, and normalization
• API integrations (GitHub, Jira, Confluence, REST/GraphQL)
• Data warehousing or data lake technologies (Snowflake, BigQuery, S3, Delta Lake, etc.)
• Familiarity with LangChain, LlamaIndex, or similar frameworks for AI agents.
• Ability to design scalable, secure, access-controlled AI architectures.

Product Experience

 (not mandatory but is a big advantage)

• Background in Product Management, Technical Marketing, Competitive Intelligence, or Product Strategy.
• Deep understanding of how PMs work: roadmaps, PRDs, features, customer requirements, and competitor analysis.

 Soft Skills

• Strong communication and synthesis abilities.
• Ability to turn chaos of information into clear narratives and structured systems.
• Ownership mindset, self-starter, and high execution velocity.
• Comfort working cross-functionally with senior stakeholders.

Nice-to-Have

• Experience in networking, cloud infrastructure, telco, or data-center technologies.
• Familiarity with DriveNets concepts: Network Cloud, DCge, DNOS, NCP, and hyperscale routing architectures.
• Experience building internal tools or AI products for technical users.

Why This Role Matters

This role positions AI as a core capability inside DriveNets Product.

The person filling it will:

• Transform PM workflows
• Shorten decision cycles
• Improve roadmap quality
• Accelerate competitive positioning
• Reduce friction between R&D and Product
• Preserve tribal knowledge
• Build the "second brain" of the entire product organization

They will be the architect of DriveNets' intelligent product knowledge platform for years to come.