Role Overview

We are looking for an experienced Product Specialist &Customer; Success Manager – Patent Search & Analytics with strong prior experience in Intellectual Property, patent search, patent analytics, and commercial patent intelligence platforms.

The ideal candidate should have approximately 10-15 years of relevant professional experience, with substantial hands-on exposure to patent search and analytics products used by patent professionals, R&D; teams, legal teams, and corporate IP departments

Experience: 10–15 years

Core domain: Patent Search / Patent Analytics / IP Intelligence

Customer-facing: Yes

Product/platform exposure: Mandatory

Product/AI evaluation: Strongly preferred

Travel: 30%–40%

This person will act as the company's Subject Matter Expert and Key Opinion Leader for patent search and analytics and will work at the intersection of:

- Patent Search & Analytics
- Product Management
- AI/Search Quality
- Benchmark Dataset Development
- Customer Success
- Product Adoption

The candidate should bring knowledge and methodologies developed through previous experience with patent search and analytics platforms and use those insights to help design, benchmark, validate, and continuously improve our AI-native patent search and analytics product. In addition, the individual will own important Customer Success responsibilities, working directly with customers to drive adoption, understand workflows, gather structured feedback, and translate customer requirements into product improvements.

Key Responsibilities Area

Act as the organization's Subject Matter Expert and Key Opinion Leader forpatent search, patent analytics, and IP intelligence.

Based on prior professional experience, the candidate should be capable of independently developing, executing, evaluating, and reviewing complex patent search methodologies.

The candidate should have hands-on experience with:

- Patentability / Novelty searches
- Prior-art searches
- Freedom-to-Operate searches
- Invalidity / Validity searches
- State-of-the-Art searches
- Technology landscape studies
- Competitor intelligence
- Portfolio analytics
- White-space analysis
- Technology trend analysis
- Patent monitoring
- Claim-focused searching
- Assignee and inventor intelligence

The individual should be highly proficient in:
- Boolean search
- Proximity operators
- Truncation and wildcard strategies
- Synonym and concept expansion
- IPC/CPC/USPC classification searching
- Citation searching
- Patent-family searching
- Assignee/inventor searching
- Claims searching
- Semantic searching
- AI-assisted search methodologies

The candidate should understand where traditional search techniques perform better and were semantic, AI, vector-based, or hybrid search techniques can improve patent discovery. Apply Previous Product Experience to Product Development A key expectation of this role is that the candidate will bring practical knowledge gained from previously using or working with established patent search and analytics products.

The candidate will use this experience to:

Identify best practices used by leading patent search platforms.





Identify limitations and workflow gaps in existing patent search products.

Recommend functionality that improves researcher efficiency.

Compare different approaches to patent search and analytics workflows.

Help Product Management define differentiated product capabilities.

Identify features that skilled patent researchers consider essential.

Evaluate whether new product capabilities meet professional search standards.

Identify unnecessary workflow complexity and opportunities for automation.

Recommend approaches for improving search-result relevance and usability.

The individual should be capable of explaining:

What established patent search platforms do well?

Where current tools create friction for professional users?

Which workflows can be significantly improved using AI?

Which workflows still require expert human review?

What capabilities are required for professional IP teams to trust an AI-enabled patent search platform?

Product Management & Product Engineering Support

Work closely with Product Management, Engineering, AI/Data Science, UX, and Patent Data teams to translate professional patent-search workflows into product capabilities.

Responsibilities may include:

Define functional requirements for patent search and analytics capabilities.

Translate real-world patent researcher workflows into product requirements.

Participate in product discovery and requirement-definition sessions.

Review product specifications from an IP-domain perspective.

Participate in feature prioritization discussions.

Conduct acceptance testing of new features.

Validate search and analytics workflows before production release.

Identify edge cases based on prior professional experience.

Evaluate whether product workflows meet the needs of professional patent researchers.

Review AI-generated outputs for technical and IP-domain accuracy.

Provide domain expertise for capabilities including but not limited to:

Natural-language patent search

Natural-language-to-Boolean query generation

Semantic patent search

Hybrid keyword and semantic search

Query expansion

Automated keyword generation

CPC/IPC recommendation

Prior-art retrieval

Search-result ranking

Patent similarity

Claim similarity

Citation analysis

Technology clustering

Patent landscapes

Assignee intelligence

Portfolio analytics

Competitive intelligence

Gold Standard Dataset Development

Own the methodology for creating Gold Standard datasets used to evaluate patent search, analytics, and AI capabilities.

The candidate should use prior search experience to determine what constitutes a genuinely relevant result rather than relying solely on automated metrics.

Benchmark Dataset Development





Create structured benchmark datasets for measuring product performance overtime.

Develop benchmark methodologies that allow search quality to be measured consistently.

Competitive Product Benchmarking

Based on prior experience using commercial patent-search and analytics platforms, the candidate will help establish a structured competitive benchmarking program.

The objective is not simply to compare feature lists, but to evaluate actual search quality, researcher productivity, analytics capability, and workflow efficiency.

Candidate must have professional experience using such platforms, that practical experience should be used to identify appropriate workflows and benchmark scenarios.

The candidate will help create standardized benchmark reports that allow Product Management and Engineering teams to understand where the platform is performing well and where improvements are required.

Search Quality & Relevance Evaluation

Own or support systematic evaluation of search-result quality. Search-quality evaluations should result in actionable recommendations for Product, Engineering, and AI teams.

Search Methodology Development

Develop standardized methodologies that represent professional best practices for different patent-search use cases. These methodologies should ultimately help Product and AI teams transform expert patent-search practices into scalable product workflows.

AI & Search Model Evaluation

Work closely with AI/Data Science teams as the IP-domain evaluator for AI-powered search capabilities.

The candidate does not need to be an AI engineer but should understand enough about modern search technologies to evaluate their outputs effectively.

Customer Success Management The candidate will also assume responsibility for Customer Success for patent search and analytics customers.

This requires significantly more than conventional account management.

The candidate should be capable of engaging customers as a patent search and analytics expert and helping them achieve meaningful outcomes using the platform.

Voice of Customer

Act as a structured bridge between customers and Product Management. Customer feedback should be translated into measurable product improvement opportunities rather than passed to Product Management as unstructured requests.

Customer Trials & Product Evaluations

Design and manage structured customer evaluation programs for the patent search and analytics platform.

Create structured evaluation forms and scoring methodologies that allow enterprise customers to provide actionable product feedback during trials and proof-of-concept engagements.

Product Training & Thought Leadership

Create domain-specific product and educational material. Represent the organization as a domain expert during customer demonstration, enterprise evaluations, customer workshop, webinars, design partner sessions, Industry discussions, conferences and seminar as per business requirements.

The individual should gradually become recognized by customers as a trustedexpert on patent search, analytics, and AI-enabled patent intelligence.

*Role may require travel 30-40% of the time.

📌 Product & Customer Success Lead (Gurugram)
🏢 Nuvo AI
📍 Gurugram