Forward Deployed Engineer - GTM

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're looking for a Forward Deployed Engineer- GTM 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 We've built two products to solve this: 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.

What You'Ll Do

Own the technical arc of the deal: discovery and the in-depth demo, the architecture discussion with the customer's engineering leaders, and the POC - all the way through to close. Win the POC on technical merit: Co-define the success criteria with the customer, run the execution tracker and the milestones, and write the integration glue, agent workflows, and eval pipelines that prove value in their environment. The goal is delivered impact, not lines of code.

Make the architecture calls that decide how the customer would run AI in production. You are the technical decision-maker in the room - the CTO in the room - and the person their engineering leaders trust. Be the technical face of TrueFoundry to enterprise customers, and earn the credibility that turns an evaluation into a signed contract.

Steer the product. You see, first-hand, what customers pull toward and where their first production win lands. Compile that field signal and bring structured, data-backed asks to TrueFoundry's engineering and product teams - your intuition helps shape the roadmap.

Who we're looking for Backend Engineering Experience: 3 to 7 years of backend software engineering experience with production systems you have shipped and owned. Strong in Python, Go, or TypeScript. Comfortable with Kubernetes or any major cloud (AWS, Azure, GCP).

Business Acumen: You don’t just question the how but also the why - discovering impact, architecture design and deal-winning opportunities. AI and ML literacy: You have worked with LLMs, agents, evals, or ML pipelines in production. Familiarity with the modern stack (vLLM, SGLang, LangChain, Triton, model serving) is a strong plus.

Design and Architecture: Comfortable leading an architecture discussion with a customer's engineering leaders, then doing the work yourself. High agency and a bias for action. We especially welcome founding engineers and CTOs of early-stage startups, as well as engineers from infrastructure, MLOps, and developer-tool companies.

Growth path Engineering ladder: Senior FDSE to Staff or Principal FDSE, with named-account ownership and architectural authority at every level. Leadership ladder: Lead FDSE to Head of FDSE, building and running the function. Cross-functional: the role builds the breadth that leads to CTO, VP of Engineering, and founder paths.