The Role :

This is a hands-on architect role - 100% hands-on. You will write code, design schemas, and ship production systems alongside the team. This is not a slide-deck or PowerPoint architect role. If you have not written code in the last 12 months, this role is not for you.

You will own the RCG implementation track within Pathfinder, design the federated knowledge graph patterns we deploy at clients, and lead technical conversations with senior client stakeholders. You will report directly to the Founder & CEO.

What You'll Do :

- Design and implement RCG schemas, ontologies, and reference patterns for client engagements

- Write production-grade Python, Cypher/Gremlin, and orchestration code (LangGraph or equivalent)

- Use AI coding tools (Claude Code, Cursor, or equivalent) as a force multiplier to ship faster without sacrificing quality

- Build and operate knowledge graphs on Neo4j and Amazon Neptune at enterprise scale

- Design federated KG architectures (Schema KG vs. Instance KG separation) for multi-tenant deployments

- Lead technical conversations with client architects, R&D directors, and CIOs

- Mentor senior engineers and elevate the team's technical depth

- Contribute to patent filings, technical white papers, and Pathfinder roadmap

Must-Haves :

- 5+ years of software engineering experience, with at least 3-4 years in AI/ML systems

- 100% hands-on - actively writing code today, not directing others to write it

- Production knowledge graph experience : designed schemas, written non-trivial Cypher/Gremlin/SPARQL, operated Neo4j, Amazon Neptune, or TigerGraph at meaningful scale

- Strong Python and modern AI tooling : LangGraph, LangChain, or equivalent agent orchestration frameworks

- Hands-on experience with KG-augmented AI : GraphRAG, ontology-driven reasoning, or KG-augmented LLM retrieval

- Daily, fluent use of AI coding tools - Claude Code, Cursor, Kiro, GitHub Copilot, or equivalent. You should be able to demonstrate how you use these tools to ship production code, including prompting strategy, multi-file refactoring, agentic workflows, and where you trust them vs. override them

- Enterprise software shipping experience : data governance, lineage, multi-tenancy, observability

Strong Preferences :

- MS or PhD in graph theory, knowledge representation, computational linguistics, or applied ML on structured data

- Open-source contributions, papers, or public technical writing

- Exposure to SAP, ERP, or enterprise data models

- Product company background : Microsoft Research India, Google, Adobe Research, Flipkart/Myntra ML, Sarvam, Krutrim, or comparable AI-first company

- AWS architecture-level depth : Bedrock, SageMaker, Neptune, Lambda, IAM