Staff/Principal Engineer – Core Engineering

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.

We're TrueFoundry, and we're building it. We're looking for a Staff/Principal Engineer our Core Engineering to join the team.

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

We've built two products to solve this:

AI Gateway is the control plane of five composable components (Prompts, LLM Gateway, MCP Gateway, Guardrails, Agent Gateway) that handle routing, orchestration, and governance.

AI Deploy is a compute layer of a Kubernetes-based platform that abstracts ML workloads as standard software primitives, so everything runs on unified infrastructure.

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.

We're looking for an Engineer who is passionate about scaling deep learning workloads, optimizing multi-GPU training, and shipping production-grade solutions. 

• 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.

• →Develop deep expertise across TrueFoundry’s platform stack  infrastructure, deployment systems, LLM/ML orchestration, observability, cost optimization, and more
• →Drive the system architecture and design for complex, distributed, cloud-native systems
• →Act as the technical point-of-contact for enterprise customer engineering needs and escalations
• →Lead and participate in design reviews, code reviews, and critical incident responses
  
• →Collaborate closely with the CTO on architectural decisions, scaling strategies, and technical roadmap prioritization
• →Guide and mentor US-based engineers across multiple initiatives, helping them deliver high-quality, scalable systems
• →Identify and drive technical debt cleanup, performance improvements, and resilience upgrades across the platform
• →Bring a product engineering mindset, ensuring that customer needs and feedback translate into scalable engineering solutions

• 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 experience building or deploying ML/GenAI applications (or closely working with ML/DS teams)
• Skilled in programming languages such as Python, Go, or typescript
  
• Solid understanding of system observability, resiliency design, and SRE practices
  
• Strong technical leadership and communication skills — able to work with both customers and engineering teams
  
• Ability to think strategically while also executing hands-on when required