{"schemaVersion":"jobsearcher.job.v1","id":"b72133f78d8b6bd82c31f642","url":"https://jobsearcher.com/jobs/b72133f78d8b6bd82c31f642","canonicalUrl":"https://jobsearcher.com/jobs/b72133f78d8b6bd82c31f642","title":"Forward Deployed Engineer - GTM","description":"About TrueFoundry\nEvery 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.\n\nThat infrastructure layer is being built right now.\n\nWe're TrueFoundry, and we're building it. We're looking for a Forward Deployed Engineer- GTM to join the team.\n\nThe Problem We're Solving\nCompanies 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.\n\nThe infrastructure to support this doesn't exist yet. You can't just duct-tape together a few API calls and call it production-ready.\n\nYou need a control plane that handles:\n\nIntelligent routing with observability, cost policies, and fallback logic\n\nCentralized tool and MCP server management with security and lifecycle controls\n\nAgent orchestration with governance and guardrails\n\nA unified compute layer to run self-hosted models, custom tools, and agents\n\nWe've built two products to solve this:\n\nAI Gateway is the control plane five composable components (Prompts, LLM Gateway, MCP Gateway, Guardrails, Agent Gateway) that handle routing, orchestration, and governance.\n\nAI Deploy is the compute layer of Kubernetes-based platform that abstracts ML workloads as standard software primitives, so everything runs on unified infrastructure.\n\nWhat you'll do\n\nOwn 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.\n\nWin 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.\n\nMake 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.\n\nBe the technical face of TrueFoundry to enterprise customers, and earn the credibility that turns an evaluation into a signed contract.\n\nSteer the product. You see, first­hand, 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.\n\nWho we're looking for\n\nBackend 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).\n\nBusiness Acumen: You don’t just question the how but also the why - discovering impact, architecture design and deal‑winning opportunities.\n\nAI 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.\n\nDesign 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.\n\nWe especially welcome founding engineers and CTOs of early‑stage startups, as well as engineers from infrastructure, MLOps, and developer‑tool companies.\n\nGrowth path\n\nEngineering ladder: Senior FDSE to Staff or Principal FDSE, with named‑account ownership and architectural authority at every level.\n\nLeadership ladder: Lead FDSE to Head of FDSE, building and running the function.\n\nCross‑functional: the role builds the breadth that leads to CTO, VP of Engineering, and founder paths. Many FDSE alumni have gone on to start their own companies.\n\n#J-18808-Ljbffr","company":"Truefoundry","rawCompany":"truefoundry","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-07-16T04:09:03.335Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Forward Deployed Engineer - GTM","description":"About TrueFoundry\nEvery 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.\n\nThat infrastructure layer is being built right now.\n\nWe're TrueFoundry, and we're building it. We're looking for a Forward Deployed Engineer- GTM to join the team.\n\nThe Problem We're Solving\nCompanies 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.\n\nThe infrastructure to support this doesn't exist yet. You can't just duct-tape together a few API calls and call it production-ready.\n\nYou need a control plane that handles:\n\nIntelligent routing with observability, cost policies, and fallback logic\n\nCentralized tool and MCP server management with security and lifecycle controls\n\nAgent orchestration with governance and guardrails\n\nA unified compute layer to run self-hosted models, custom tools, and agents\n\nWe've built two products to solve this:\n\nAI Gateway is the control plane five composable components (Prompts, LLM Gateway, MCP Gateway, Guardrails, Agent Gateway) that handle routing, orchestration, and governance.\n\nAI Deploy is the compute layer of Kubernetes-based platform that abstracts ML workloads as standard software primitives, so everything runs on unified infrastructure.\n\nWhat you'll do\n\nOwn 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.\n\nWin 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.\n\nMake 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.\n\nBe the technical face of TrueFoundry to enterprise customers, and earn the credibility that turns an evaluation into a signed contract.\n\nSteer the product. You see, first­hand, 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.\n\nWho we're looking for\n\nBackend 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).\n\nBusiness Acumen: You don’t just question the how but also the why - discovering impact, architecture design and deal‑winning opportunities.\n\nAI 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.\n\nDesign 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.\n\nWe especially welcome founding engineers and CTOs of early‑stage startups, as well as engineers from infrastructure, MLOps, and developer‑tool companies.\n\nGrowth path\n\nEngineering ladder: Senior FDSE to Staff or Principal FDSE, with named‑account ownership and architectural authority at every level.\n\nLeadership ladder: Lead FDSE to Head of FDSE, building and running the function.\n\nCross‑functional: the role builds the breadth that leads to CTO, VP of Engineering, and founder paths. Many FDSE alumni have gone on to start their own companies.\n\n#J-18808-Ljbffr","datePosted":"2026-07-16T04:09:03.335Z","dateModified":"2026-07-16T04:09:03.335Z","hiringOrganization":{"@type":"Organization","name":"Truefoundry","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"b72133f78d8b6bd82c31f642"},"url":"https://jobsearcher.com/jobs/b72133f78d8b6bd82c31f642"}}