Principal AI Architect, Agentic Platform

We are looking for a Principal AI Architect, Agentic Platform to define the technical foundation for 6sense's next generation of agentic AI.

This is the most senior AI individual contributor role in Engineering. You will establish the architecture, design patterns, runtime standards, evaluation practices, security controls, and governance mechanisms that enable teams across 6sense to build and operate production-grade AI agents safely and efficiently.

You will own the architectural direction for our agentic platform, including orchestration, tools and skills, memory and context, evaluation and observability, security and privacy, guardrails, AI governance, and model strategy.

This is a hands-on Principal role. You will not manage a team, but you will influence architecture across the organization through reference implementations, RFCs, technical reviews, prototypes, mentorship, and deep involvement in complex production systems.

What You'll Own

Agentic Architecture & Design Patterns

- Define the platform-wide architecture for how agents are composed, orchestrated, and executed.

- Establish clear boundaries between reasoning, orchestration, state, tools, and execution.

- Create and maintain an agentic design-pattern catalog covering approaches such as ReAct, plan-and-execute, orchestrator-worker, routing, prompt chaining, fan-out/fan-in, reflection, evaluator-optimizer, and multi-agent handoffs.

- Guide teams toward the simplest architecture that solves the problem, introducing multi-agent systems only when there is a clear technical need.

- Design memory and context architectures covering working, episodic, and semantic memory; context compaction; retrieval grounding; subagent isolation; and tenant-scoped context.

- Publish reference architectures, RFCs, implementation guides, and reusable patterns.

- Lead architecture reviews for agentic systems across Engineering.

Agentic Runtime & Developer Platform

- Own the architecture and standards for LangGraph, including typed state graphs, conditional routing, subgraphs, checkpointing, durable execution, human-in-the-loop workflows, streaming, replay, and time-travel debugging.

- Establish engineering standards for LangChain and determine where framework abstractions provide value versus direct model/provider SDKs.