Senior AI/ML Engineer — LLM & Agent Stack (Customer Facing)
Design and implement the infrastructure for enterprise-grade AI agent systems, integrating LLMs, tools, and governance controls while working directly with customers to deploy production-ready solutions.
- Compensation
- Not disclosed
- Location
- San Mateo, San Francisco Bay Area
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- 5–10 years of software engineering with substantial experience building distributed systems, infra, or ML platforms.
- Deep practical experience integrating and deploying LLMs in production (RAG, retrieval, embeddings pipelines).
- Hands-on experience with agent orchestration frameworks (LangGraph / LangChain or custom agent runtimes) and stateful workflow design.
- Strong systems knowledge: Kubernetes, container orchestration, service meshes, and performance tuning.
- Proven track record building observability, cost controls, and policy enforcement for production services.
Full 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 Senior AI/ML Engineer — LLM & Agent Stack (Customer-Facing) to join the 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.
Role summary
You’ll design and own core components that enable enterprise customers to run production agentic AI safely and efficiently on TrueFoundry. This includes building robust orchestration for multi-step agents (graph/stateful workflows), model/routing logic, observability and policy enforcement (cost, data residency, rate limiting), and integrating upstream tooling like LangGraph, LangChain, vector stores, and specialized LLM runtimes. This is a customer-facing role where you'll work closely with TrueFoundry's enterprise customers. You may also need to write code in their environments.
What you’ll do
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Architect and implement scalable agent orchestration patterns (graph-based executors, state management, multi-agent coordination) for production workloads.
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Own critical integrations: model adapters, LLM gateway hooks, vector DBs, tools & external APIs, and the platform’s LLMops flows.