Principal Engineer, Agent Platform

About the Role

We are building the enterprise AI agent platform that teams across the company will use to create, deploy, govern, and operate AI-powered solutions at scale. As a Principal Engineer, you will help define the technical foundation for agent development across the organization, building the services, frameworks, and guardrails that make AI agents secure, reliable, observable, and easy to adopt.

This is a hands-on engineering role focused on architecture, software design, and platform development. You will work across AI, distributed systems, cloud infrastructure, security, and governance to deliver a platform that enables product and engineering teams to move quickly while meeting enterprise standards for security, compliance, and operational excellence.

What You'll Do

Design and build core platform services that enable enterprise AI agent development and operations

Define the architecture, engineering patterns, and technical standards for the AI agent platform

Develop and maintain a centralized model gateway for routing, governance, resiliency, and cost management

Build agent runtime capabilities that support long-running workflows, orchestration, and human-in-the-loop processes

Design secure identity, authorization, and policy enforcement mechanisms for agents and tools

Establish platform capabilities for context management, memory, retrieval, and data isolation

Create testing, evaluation, and release frameworks that ensure agent quality, safety, and performance

Implement observability, auditability, and operational tooling for monitoring and troubleshooting agent behavior

Partner with Security, Data Governance, and Cloud Infrastructure teams to define platform controls and guardrails

Mentor engineers, influence technical direction, and raise engineering standards across multiple teams

Who You Are

Extensive experience building and operating large-scale distributed systems in production

Strong software engineering background with expert-level Python development skills

Hands-on experience delivering production LLM, generative AI, or agent-based solutions

Deep understanding of agent architectures, orchestration patterns, and enterprise AI platforms

Experienced with retrieval systems, embeddings, vector search, and context management strategies

Knowledgeable in AI evaluation, testing methodologies, and quality assurance for non-deterministic systems

Proficient with Google Cloud services including Vertex AI, Gemini, GKE, Cloud Run, BigQuery, and Pub/Sub

Experienced with cloud security, workload identity, OAuth, policy-as-code, and secure-by-design architectures

Strong understanding of distributed system reliability patterns, including resiliency, retries, observability, and fault tolerance

Proven ability to influence technical direction, drive adoption of architectural standards, and lead through expertise rather than authority