Product Lead



About the RoleWe are building a Context Engine that enables Agentic AI systems and LLMs to reason with reliable, structured and domain-specific context.

The Context Engine uses Ontology, Knowledge Graphs and semantic relationships to represent domain knowledge and provide AI systems with the right context at the right time.

We are looking for a Product Lead who can work at the intersection of Product, Ontology/KG, AI, Engineering and Customer POCs.

This is not a conventional project-management role. You will be expected to understand the technology at a conceptual and working level, reason with engineering teams, conduct research, contribute to ontology/KG development, test ideas, document the technology, interact with users and help shape the MVP roadmap.

You will work closely with the CPO, founders/ideators and engineering teams to take the Context Engine from concept → MVP → validated POCs → production handover.

What You Will Do1. Own Day-to-Day MVP Product Execution· Translate the Context Engine vision into clear MVP capabilities, use cases and build priorities.

· Work closely with the CPO and founders to convert ideas and hypotheses into an actionable roadmap.

· Track MVP progress, dependencies, risks and decisions.

· Identify gaps, ambiguity and blockers and drive them toward resolution.

· Ensure that the MVP remains focused on its intended customer and business outcomes.

· Participate actively in product and technical discussions rather than simply tracking tasks.

- Work Closely with Ontology & Knowledge Graph Teams· Understand and contribute to the design of domain ontologies and Knowledge Graphs.

· Help identify entities, classes, properties and relationships required to represent domain knowledge.

· Review and refine semantic relationships and terminology.

· Contribute to manual triple definition and semantic modelling.

· Ensure that relationships accurately represent the intended meaning and domain behaviour.

· Maintain consistency in terminology and ontology definitions.

· Work with engineers to translate domain concepts into machine-readable representations.

- Research & Technical Reasoning· Research emerging approaches in Ontology, Knowledge Graphs, RDF / semantic technologies, LLM grounding, RAG, Agentic AI, Context Engineering and Knowledge Representation.

· Compare alternative technical approaches and communicate their implications to the team.

· Form hypotheses and help design experiments to validate them.

· Analyze test results and convert learnings into product or technical improvements.

· Challenge assumptions constructively when evidence suggests a different approach.

- Facilitate Between Engineering Teams· Act as the connective layer between the teams involved in building the Context Engine.

· Work with Ontology/KG engineers, backend/application engineers, AI/LLM engineers, LinkEye engineering/product teams,



testing/QA teams and production/DevOps teams.

· Facilitate understanding and decisions rather than simply passing requirements between teams.

· Ask and drive clarity around the problem, assumptions, evidence, customer need, technical implications and MVP priority.

- Customer Engagement & POCs· Participate in customer discovery and technical discussions.

· Understand customer problems and identify the context required to solve them.

· Support and drive Context Engine POCs.

· Define POC scenarios, test cases and expected outcomes.

· Work with users to understand failures, gaps and unexpected behaviour.

· Translate customer feedback into actionable insights for the build team.

· Identify patterns across POCs that can influence the product roadmap.

- Product & Technical Documentation· Own and maintain documentation required to build, explain and evolve the Context Engine.

· Product documentation: product vision, problem statement, use cases, MVP scope, capabilities, roadmap, POC scenarios, success criteria and limitations.

· Technical documentation: architecture, data/context flows, ontology/KG concepts, semantic relationships, integration points, technical decisions, experiments, test methodology and known limitations.

· Ontology documentation: entity/class definitions, property definitions, relationship definitions, semantic rules, examples and modelling guidelines.

· Explain technically complex concepts clearly to both engineers and non-technical stakeholders.

- Product Articulation & Marketing Support· Work with the CPO and marketing/content teams to articulate what the Context Engine is, why it is required for Agentic AI, what problem it solves, how it differs from conventional RAG/LLM approaches, what the MVP demonstrates and what customer use cases it addresses.

· Convert complex technical concepts into clear, accurate and compelling product narratives without oversimplifying the technology.
- Production Handover· Define MVP acceptance criteria.

· Ensure product and technical documentation is complete.

· Capture architectural and operational learnings.

· Document known limitations and future requirements.

· Work with the production team to prepare the handover.

· Support the transition from experimental MVP to production-ready product.

What We Are Looking ForCore Requirements· Conceptual understanding of Ontology and Knowledge Graphs.

· Ability to reason about semantics, entities, relationships and domain meaning.

· Ability to conduct technical research independently.





· Ability to translate ambiguous ideas into structured product requirements and experiments.

· Ability to understand complex technical concepts and explain them clearly.

· Solid analytical and reasoning ability.

· Excellent written and spoken English.

· Strong technical writing capability.

· Comfortable working with engineers and technical teams.

· Strong collaboration and mediation skills.

· Comfortable interacting with customers/users during POCs.

· Strong ownership mindset.

Highly Preferred· Prior experience working with the network-management/domain context.

· Understanding of RDF, OWL, SPARQL or other semantic technologies.

· Aware of Neo4j or other Knowledge Graph platforms.

· Understanding of LLMs, RAG and Agentic AI.

· Experience working with AI/ML or developer-oriented products.

The Kind of Person We Are Looking ForYou may be a good fit if you enjoy moving between different worlds:

Domain knowledge ↔ Ontology ↔ Engineering ↔ Product ↔ Customer

You do not have to be the deepest expert in every technology. But you should be someone who can:

· Understand

· Question

· Research

· Reason

· Model

· Test

· Document

· Communicate

You should enjoy working in an environment where the product is still being discovered and where new questions are often more valuable than immediately having answers.

You should be comfortable saying: "I don’t know yet. Let me research it, test the assumption and come back with evidence."

What Success Looks Like· The Context Engine MVP has a clear and continuously evolving product definition.

· Ontology/KG concepts are semantically consistent and well documented.

· Engineering teams have clarity on what they are building and why.

· Technical decisions are supported by research and experimentation.

· MVP progress, risks and dependencies are visible.

· Customer POCs generate meaningful product learning.

· Product and technical documentation are maintained throughout the build.

· The CPO and founders have a reliable partner for day-to-day MVP execution.

· The validated MVP can be confidently handed over to the production team.

This Role Is NOT· A Jira/task tracking role

· A Scrum Master role

· A conventional project coordinator role

· A documentation-only role

· A pure ontology/KG engineering role

· A pure Product Manager role

It is a hands-on technical product and knowledge role that combines domain understanding, semantic modelling, research, product thinking, technical communication and cross-team collaboration.

Suggested Experience1-2 years of relevant experience preferred.

Candidates with strong analytical ability, ontology/KG exposure and relevant Product domain experience may be considered even if they do not match every item above.

Role DetailsReporting: CPO / Product Leadership

Employment Type: [Full-time]

- Location: [Hybrid]

📌 Product Lead (Karnataka)
🏢 LinkEye
📍 Karnataka