Senior Platform Engineer (US/Canada)

About the Role

This is a contractor role through X-Team. As a Senior Platform Engineer you will build and operate the centralized Kong AI Gateway that fronts all enterprise model traffic. You will sit at the center of the enterprise AI infrastructure—owning gateway proxy operations, promoting routing configurations from stage to production, and enforcing zero-direct-credential access policies.

Your work will directly enable autonomous agents and backend services by managing API key lifecycles, maintaining the Model Context Protocol (MCP) server registry, and instrumenting token-level cost attribution across the entire organization. Most Important 5+ Years of Experience: Proven background in platform engineering, API infrastructure, or high-scale backend production systems.

API Gateway Operations: Production experience configuring, deploying, and operating API gateways at scale (Kong strongly preferred; Envoy, Apigee, or Istio accepted). LLM Provider Integration: Hands-on experience integrating model provider APIs (Anthropic, AWS Bedrock, OpenAI) into enterprise application architectures.

Auth & Credential Management: Deep working knowledge of RBAC/OIDC protocols, API key lifecycle management, and secret/key rotation practices. Caching & Performance: Experience deploying caching layers (Redis or similar) for latency reduction, semantic caching, or cost optimization. Core Languages: Strong proficiency in Python or Go for building platform automation, custom gateway plugins, and core infrastructure tooling.

Nice to Have

Familiarity with Model Context Protocol (MCP) or comparable service-registry and service-mesh patterns for autonomous AI agents. Advanced AI Caching: Hands-on exposure to vector databases or semantic caching mechanisms specifically tuned for GenAI/LLM payloads. AI Proxy Tooling: Prior exposure to modern AI proxy frameworks or AI management platforms (e.

g., Initializ AI, Portkey, LiteLLM). Personal Traits Problem-Solving & Value-Driven Communicator: Possesses strong behavioral and technical communication skills; able to articulate complex technical decisions, approach problem-solving methodically using frameworks like the STAR method, and clearly demonstrate business value.

Agile & Adaptable: Thrives and stays comfortable operating within a fast-moving platform engineering team with continuously evolving standards, tools, and practices. Security & Operational Mindset: Prone to proactive risk management; takes a rigorous approach to enterprise security, zero-trust architectures, credential lifecycle management, and high-availability systems.

Cost & Ownership Conscious: Possesses a strong sense of end-to-end accountability for production systems, keeping a close eye on system performance, token usage, and granular cost attribution across teams and agents. Collaborative Platform Facilitator: Acts as a trusted partner to downstream internal development and AI agent teams, making it easy and secure for other engineers to leverage central AI infrastructure without friction.