Principal Engineer - Inference Control Plane (Canada & United States)

About the Role

This is a contractor role through X-Team. As a Principal Engineer for the Inference Control Plane, you will own the architectural vision and hands-on execution of our core AI infrastructure. You will be responsible for designing, building, and operating our Partner's Kong AI Gateway—serving as the central ingress point for all model traffic.

In this dual-role capacity, you will operate both as a high-level architect/consultant advising cross-functional teams and as a hands-on builder driving technical execution. You will establish our multi-provider routing strategies, enforce API credential governance, build our Model Context Protocol (MCP) gateway, and implement cost-optimization and attribution patterns at scale while mentoring senior platform engineers on the team.

Most Important 8+ years of experience in platform engineering, API infrastructure, or distributed systems, including technical leadership of engineering teams. Proven background building or operating API gateways at scale (Kong strongly preferred; Envoy, Apigee, or similar accepted). Hands-on experience integrating multiple LLM providers (Anthropic, OpenAI, AWS Bedrock) with failover strategies.

Deep understanding of RBAC, OIDC, API key lifecycle management, and credential governance patterns. Experience implementing semantic caching, request/response caching, or equivalent cost-optimization strategies for high-volume traffic. Familiarity with MCP (Model Context Protocol) or comparable tool-registry/service-mesh architectures.

Strong hands-on coding skills in Python or Go for platform tooling, custom plugins, and automation. Proven track record of setting architecture standards, mentoring senior engineers, and driving cross-team alignment. Degree in Computer Science, a related technical field, or equivalent hands-on industry experience.

Nice to Have

Experience with Initializ AI platform/tooling. Prior experience building centralized AI gateways or LLM proxy layers in enterprise environments. Deep knowledge of observability frameworks (Open. Telemetry) applied to LLM tracing and latency monitoring. Contributions to open-source API gateway plugins, MCP tools, or cloud-native infrastructure projects.

Personal Traits Able to articulate how their technical choices drive tangible business outcomes and efficiency. Seamlessly transitions between high-level architectural consulting and deep, hands-on technical execution. Can clearly explain complex infrastructure concepts, trade-offs, and strategies to both executive leaders and engineering peers.

Takes ownership of complex, evolving technologies with a bias toward clean architecture, reliability, and security. Enjoys elevating team capabilities through active mentorship, code reviews, and setting clear technical benchmarks.