Principal Engineer, Backend Engineering (Remote)

• Set the technical direction for the AI proxy platform across three pillars: cost efficiency and ROI insights, secure AI usage, and AI context integration.

• Design and deliver the proxy service architecture targeting 99.95% or higher availability, while maintaining sub-second latency to preserve developer experience across all routed AI traffic.

• Own the cost-efficiency stack: integration with internal usage quota enforcement systems with near real-time cap enforcement, semantic caching and context reuse across tools, model routing and downgrade policies, and workflow-level cost attribution.

• Define the security integration surface so that security, compliance, and supply chain governance teams can enforce policies at machine speed across all internal AI tools through shared hooks, rather than building bespoke runtimes per tool.

• Drive the context integration layer: connecting with context infrastructure and repository harness, enabling skills and tool registry sharing across AI tools, progressive disclosure of context, and agent quality benchmarking across tools and repositories.

• Lead technical decisions on cloud infrastructure integration for model execution, output token optimization strategies, intelligent model routing, and context compression tooling rollout.

• Partner with AI platform, security, compliance, and developer tooling teams to maintain alignment across a multi-team initiative with significant cross-functional coordination requirements.

• Mentor and uplift a team of engineers across multiple delivery streams covering reliability, usage governance, and proxy core, while reserving sufficient capacity for system reliability alongside feature delivery.

• Establish and own the telemetry and observability stack: dashboards for agent and CI traffic, cache hit rates, workflow effectiveness, cost per successful workflow, and ROI attribution by tool, team, and user.

Benefits & Perks

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