Job Description

Product Lead

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 Job Description

About the Role n

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

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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.

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

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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.

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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 n

· Translate the Context Engine vision into clear MVP capabilities, use cases and build priorities.

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

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· Track MVP progress, dependencies, risks and decisions.

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

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

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

2. Work Closely with Ontology & Knowledge Graph Teams n

· Understand and contribute to the design of domain ontologies and Knowledge Graphs.

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

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· Review and refine semantic relationships and terminology.

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· Contribute to manual triple definition and semantic modelling.

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

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· Maintain consistency in terminology and ontology definitions.

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

3. Research & Technical Reasoning n

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

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

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· Form hypotheses and help design experiments to validate them.

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

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· Challenge assumptions constructively when evidence suggests a different approach.

4. Facilitate Between Engineering Teams n

· Act as the connective layer between the teams involved in building the Context Engine.

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



testing/QA teams and production/DevOps teams.

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

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

5. Customer Engagement & POCs n

· Participate in customer discovery and technical discussions.

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

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· Support and drive Context Engine POCs.

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· Define POC scenarios, test cases and expected outcomes.

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

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

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

6. Product & Technical Documentation n

· Own and maintain documentation required to build, explain and evolve the Context Engine.

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

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

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

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

7. Product Articulation & Marketing Support n

· 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.

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· Convert complex technical concepts into clear, accurate and compelling product narratives without oversimplifying the technology.

8. Production Handover n

· Define MVP acceptance criteria.

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· Ensure product and technical documentation is complete.

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· Capture architectural and operational learnings.

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· Document known limitations and future requirements.

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· Work with the production team to prepare the handover.

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

What We Are Looking ForCore Requirements n

· Conceptual understanding of Ontology and Knowledge Graphs.

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

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· Ability to conduct technical research independently.

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

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

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· Robust analytical and reasoning ability.

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· Excellent written and spoken English.

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· Strong technical writing capability.

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· Comfortable working with engineers and technical teams.

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· Strong collaboration and mediation skills.

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· Comfortable interacting with customers/users during POCs.

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· Strong ownership mindset.

Highly Preferred n

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

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

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· Aware of Neo4j or other Knowledge Graph platforms.

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· Understanding of LLMs, RAG and Agentic AI.

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

The Kind of Person We Are Looking For n

You may be a good fit if you enjoy moving between different worlds:

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Domain knowledge ↔ Ontology ↔ Engineering ↔ Product ↔ Customer

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

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· Understand

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· Question

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· Research

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· Reason

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· Model

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· Test

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· Document

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· Communicate

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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.

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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 n

· The Context Engine MVP has a clear and continuously evolving product definition.

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

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

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· Technical decisions are supported by research and experimentation.

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· MVP progress, risks and dependencies are visible.

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· Customer POCs generate meaningful product learning.

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· Product and technical documentation are maintained throughout the build.

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

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

This Role Is NOT n

· A Jira/task tracking role

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· A Scrum Master role

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· A conventional project coordinator role

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· A documentation-only role

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· A pure ontology/KG engineering role

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· A pure Product Manager role

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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 Experience n

1-2 years of relevant experience preferred.

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

Role Details n

Reporting: CPO / Product Leadership

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Employment Type: [Full-time]

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- Location: [Hybrid]
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📌 Product Engineer (Karnataka)
🏢 LinkEye
📍 Karnataka