we are 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 our company 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 company 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 our company PM chatbot capable of:
Understanding our company 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.
This position sits at the intersection of AI, data engineering, product strategy, and organizational knowledge management. You will function as the AI engine behind our company 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 company 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 our company PM chatbot capable of:
Understanding our company 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.
Requirements:
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.
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.
This position is open to all candidates.
