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Staff /Principal Engineer – Core Team

TrueFoundry
CompanyTrueFoundry
CategoryEngineering
LocationSan Francisco
RemoteOn-site (inferred)
EmploymentNot stated
LevelLead
SalaryNot stated by the employer
Posted28 Apr 2025
Last verified5 Aug 2026
SourceEmployer ATS (greenhouse)
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Description
About TrueFoundry Every production AI system, whether it's powering customer support, writing code, analyzing financial data, or diagnosing medical conditions, needs the same foundational infrastructure.A way to route between models. A way to manage tools and integrate them securely. A way to orchestrate agents and enforce governance. A unified compute layer to run it all. That infrastructure layer is being built right now. We are looking for a Staff/Principal Engineer – Core Team. The Problem We're Solving Companies are moving beyond simple chatbots to production agentic systems. These systems route between OpenAI, Anthropic, Google, and self-hosted models. They integrate dozens of tools via protocols like MCP. They orchestrate multi-agent workflows where agents coordinate with other agents. The infrastructure to support this doesn't exist yet. You can't just duct-tape together a few API calls and call it production-ready. You need a control plane that handles: Intelligent routing with observability, cost policies, and fallback logic Centralized tool and MCP server management with security and lifecycle controls Agent orchestration with governance and guardrails A unified compute layer to run self-hosted models, custom tools, and agents AI Gateway is the control plane: five composable components (Prompts, LLM Gateway, MCP Gateway, Guardrails, Agent Gateway) that handle routing, orchestration, and governance. We're Series A, backed by Intel Capital and Sequoia. Companies like CVS, Mastercard, Siemens, Paytm, Synopsys, and Zscaler run production AI workloads on our platform.   The Role: Solve some of the most complex Engineering problems and drive it alongside a team of engineers & ML researchers. Build a deep, holistic understanding of the TrueFoundry platform across all components and shape the product vision and implementation. Act as the technical face of engineering for customer-related discussions and escalations Guide and unblock engineers across projects in the US region Partner closely with our CTO and India-based engineering team to drive system design, architecture, and implementation of complex products Lead technical design, critical customer problem-solving, and platform scalability initiatives end-to-end This is a high-ownership, high-impact role designed for an engineer who loves combining world-class systems thinking with real-world execution. What You’ll Do: Build and scale TrueFoundry's MCP Gateway and Agentic Gateway, enabling secure, reliable, and scalable AI agent interactions. Design and develop cloud-native, distributed systems that power AI agents, tool integrations, and enterprise AI workloads. Build core capabilities such as authentication, authorization, routing, observability, security, and multi-tenant infrastructure for the gateway platform. Collaborate closely with the CTO to shape the technical architecture, product roadmap, and long-term platform vision. Drive architectural decisions, participate in design and code reviews, and ensure high engineering standards across the platform. Work closely with enterprise customers to understand their AI infrastructure needs and translate feedback into scalable platform capabilities. Mentor engineers across teams, helping them build high-quality, reliable, and maintainable systems. Continuously improve platform performance, reliability, scalability, and developer experience while reducing technical debt. Stay at the forefront of emerging AI infrastructure, Model Context Protocol (MCP), and agentic systems, bringing new ideas into the product Who You Are: 8+ years of strong backend/systems engineering experience at top technology companies or startups Deep expertise in distributed systems, cloud-native architectures, and scalable system design Strong working knowledge of Kubernetes, containerized workloads, and infrastructure engineering Practical