Designation: Principal AI Engineer (Knowledge Graph & Agentic Systems)

Role Overview

Looking for a Principal AI Engineer – Knowledge Graph & Agentic Systems to own the evolution and implementation of the RCG architecture within Pathfinder.

This is a 100% hands-on architect role. The ideal candidate must be actively writing production code, designing schemas, and building production systems alongside engineering teams.

The role involves designing federated knowledge graph architectures, developing agentic AI systems, working with enterprise-scale knowledge graphs, and leading technical discussions with senior client stakeholders.

The position will report directly to the Founder & CEO.

Key Responsibilities

- Design and implement RCG schemas, ontologies, and reference patterns for client engagements.
- Write production-grade Python, Cypher/Gremlin, and orchestration code using LangGraph or equivalent frameworks.
- Use AI coding tools such as Claude Code, Cursor, Kiro, GitHub Copilot, or equivalent to accelerate production development.
- Build and operate enterprise-scale knowledge graphs using Neo4j, Amazon Neptune, or similar platforms.
- Design federated knowledge graph architectures, including Schema KG and Instance KG separation for multi-tenant deployments.
- Develop and implement GraphRAG, ontology-driven reasoning, and KG-augmented LLM retrieval solutions.
- Lead technical discussions with client architects, R&D; directors, CIOs, and other senior stakeholders.
- Mentor senior engineers and strengthen the team's technical capabilities.
- Contribute to patent filings, technical white papers, and the Pathfinder product roadmap.
- Ensure enterprise systems meet requirements related to data governance, lineage, multi-tenancy, and observability.

Mandatory Requirements

- 8–12 years of software engineering experience, including at least 3–4 years of AI/ML systems experience.




- Must be 100% hands-on and actively writing production code.
- Proven production experience with Knowledge Graphs.
- Experience designing knowledge graph schemas and writing non-trivial Cypher, Gremlin, or SPARQL queries.
- Hands-on experience with Neo4j, Amazon Neptune, TigerGraph, or comparable knowledge graph platforms at meaningful scale.
- Strong programming expertise in Python.
- Robust experience with LangGraph, LangChain, or equivalent agent orchestration frameworks.
- Hands-on experience with GraphRAG, ontology-driven reasoning, or knowledge graph-augmented LLM retrieval.
- Daily working experience with AI coding tools such as Claude Code, Cursor, Kiro, GitHub Copilot, or equivalent.
- Ability to demonstrate practical use of AI coding tools for prompting, multi-file refactoring, agentic workflows, and production development.
- Enterprise software development experience involving data governance, data lineage, multi-tenancy, and observability.
- Bachelor's degree in Computer Science, Mathematics, or Computational Linguistics from IIT, IISc, IIIT-H, BITS Pilani, NIT, or an international equivalent.

Strongly Preferred

- MS or PhD in Graph Theory, Knowledge Representation, Computational Linguistics, or Applied ML on Structured Data.
- Open-source contributions, research papers, or public technical writing.
- Experience with SAP, ERP, or enterprise data models.
- Product-company experience from AI/technology-focused organizations or comparable AI-first companies.
- Robust AWS architecture experience, particularly with:
- AWS Bedrock
- Amazon SageMaker
- Amazon Neptune
- AWS Lambda
- AWS IAM

Ideal Candidate Profile

- The ideal candidate is a hands-on AI/Software Architect with deep expertise in Knowledge Graphs, agentic AI, and enterprise software systems.
- Candidates should have a strong production track record and be comfortable moving between architecture design, schema development, coding, system implementation, and client-facing technical discussions.

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