GTM Engineer
Nash
- Location
- United States
- Work style
- Remote only
- Job type
- Full time
- Posted
- Oct 30
- 1 day ago
Career path
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About the company
Nash
Information technology and services · 2 to 10 employees
NASH IS THE PLATFORM THAT POWERS MODERN LOGISTICS. Commerce has inverted. For decades, customers came to where products and services were. Now products and services come to them, on their terms, in real time. That shift has turned every company into a logistics company, even though almost none of them were built to be one. Couriers, fleets, gig workers, parcel carriers, in-store labor, and increasingly autonomous systems all have to be coordinated in real time, against tighter windows and rising expectations, with hard-fought customer trust on the line. Nash unifies decisioning, execution, and capacity into a single programmable platform. Real-time, AI-native intelligence determines what should happen, operational control executes it, and the platform dynamically orchestrates capacity from any source: a company's own fleets, partners, or the Nash delivery network. Whether a job involves a courier, a gig driver, an internal fleet, a store employee, a technician, or an autonomous vehicle, Nash selects the right resource and manages execution through completion. We power delivery and logistics for some of the most recognizable brands in commerce, including Walmart, Urban Outfitters, 7-Eleven, and Woolworths, alongside platforms like Shopify and Toast. Over the next decade, logistics will become as foundational to commerce as payments, cloud, and connectivity. Nash is the platform that powers it. Nash was founded in 2021 by Mahmoud Ghulman (2x Founder, MIT) and Aziz Alghunaim (2x Founder, 2x YC, Ex-Palantir, MIT) and is backed by Y Combinator, a16z, and other top investors. We are headquartered in San Francisco.
What you'll do
- Build and run the AI agents that work across our GTM motion: account research, signal qualification, message construction, routing and reply handling, from design through evals, rollout and the monitoring that keeps them honest
- Build the infrastructure to run paid and ABM as one system: audiences generated from the CRM, campaigns launched and paused by rules you write, engagement flowing back into the agents, and spend tied to accounts worked and pipeline created
- Own the account context layer every agent and campaign is grounded in: entity resolution, evidence typing, freshness and provenance, and the segment, industry, region and product rules that define our market
- Build on GTM OS, our internal platform, and make what it can do available to sales and marketing inside the tools they already use
- Be the technical owner of our go-to-market systems, the CRM and everything connected to it, from the data model and routing logic to the integrations and automations that keep the whole stack current and consistent
- Own sending infrastructure and deliverability: domain strategy, warming, suppression and sender reputation across every program that sends
- Hold the production bar: evals, observability, permissions and auditability, so the system reports its own failures before a rep finds them
- Be measured on what the motion produces: reply and meeting rates, pipeline and revenue, cost per account worked. Agent reliability and data quality are how you get there
- WHAT YOU'LL BRING
- A go-to-market record: outbound, paid, ABM or lifecycle programs you ran, with the pipeline they produced and the systems you built to run them
- Software you shipped and kept running: a service, agent or pipeline in production that other people depended on, with something we can look at
- Outbound that scales and still reads like a person: sequences triggered by something that just changed for the buyer and tied to what we sell, reply rates to show for them, and the judgment to pull apart a message that is not landing
- Paid media fluency: you have run budgets and built audiences, and you know which decisions should stay with a person
- Hands-on experience applying AI to go-to-market systems: agents, LLM-based automation, MCP-style integrations, and the evals that tell you whether any of it works
- Fluency in Python or TypeScript, and daily work with Claude Code, Cursor or equivalent, with specific opinions about where the tooling fails
- Integration experience: you have built and debugged integrations through APIs and understand auth, rate limits, sync direction and failure modes
- Salesforce as a developer: the data model, the API, and Apex, or the track record to pick it up fast
- Data fluency: SQL, warehouse concepts, and the habit of tracing a data quality issue from source to destination
- You can turn a vague request into scoped work and explain the tradeoffs
What you need
- A go-to-market record: outbound, paid, ABM or lifecycle programs you ran, with the pipeline they produced and the systems you built to run them
- Software you shipped and kept running: a service, agent or pipeline in production that other people depended on, with something we can look at
- Outbound that scales and still reads like a person: sequences triggered by something that just changed for the buyer and tied to what we sell, reply rates to show for them, and the judgment to pull apart a message that is not landing
- Paid media fluency: you have run budgets and built audiences, and you know which decisions should stay with a person
- Hands-on experience applying AI to go-to-market systems: agents, LLM-based automation, MCP-style integrations, and the evals that tell you whether any of it works
- Fluency in Python or TypeScript, and daily work with Claude Code, Cursor or equivalent, with specific opinions about where the tooling fails
- Integration experience: you have built and debugged integrations through APIs and understand auth, rate limits, sync direction and failure modes
- Salesforce as a developer: the data model, the API, and Apex, or the track record to pick it up fast
- Data fluency: SQL, warehouse concepts, and the habit of tracing a data quality issue from source to destination
- You can turn a vague request into scoped work and explain the tradeoffs
Key skills
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Perks
- Equity
- Flexible paid time off
- Vision insurance
- Quarterly broader team on-sites
See full description on company page, apply now