Join Nash as a GTM Engineer to build and run AI agents that enhance our go-to-market systems in a fully remote environment.
Posted by employer 2 days ago
First seen on Joblaze 1 day ago
Last verified on the company career page 1 day ago
Skills & Technologies
What you'll build
Must have
Nice to have
AI in the day-to-day
Hands-on experience applying AI to go-to-market systems: agents, LLM-based automation, MCP-style integrations.
Not disclosed in this posting: compensation, years of experience, visa sponsorship.
Benefits
Joblaze summary
The GTM Engineer at Nash is responsible for developing and managing AI agents that streamline the company's go-to-market processes, ensuring efficient account research, signal qualification, and message handling. This role requires proficiency in Python or TypeScript, experience with CRM systems like Salesforce, and a solid background in outbound and paid media strategies. Ideal candidates will have a proven track record in building and maintaining production-level systems that drive pipeline and revenue. Nash, an early-stage logistics platform, emphasizes a data-driven approach to enhance its operational capabilities.
Joblaze insights
Quick facts
From the original posting
THE ROLE
Growth owns the systems that power our go-to-market motion: our CRM, connected to enrichment, sales engagement, outbound agents, lifecycle, routing, visitor intelligence and paid, with GTM OS, our internal platform, tying them together. We are hiring a GTM Engineer to run that motion and build the agents and data layer it depends on.
Nash builds the autonomic logistics platform: a system that senses what is happening across a network, decides what to do about it and adjusts as the results come back, without waiting to be told. Our go-to-market should run the same way. A signal comes in, an agent decides what to do with it, the rep gets the account ready to work, and every outcome writes back so the next decision is better than the last.
Most of the pieces exist. GTM OS is in production, the agents run, the stack is connected. Your job is to turn them into one reliable engine that produces pipeline, hold it to a production bar, then decide what it does next.
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
HOW TO APPLY
Send us your resume, links to things you have built and kept running (a repo, a live service, an agent, a sequence with its results), and a short note on the system or motion you are most proud of and why. If you would rather skip the cover letter, send a Loom walking us through a piece of work, or a Replit prototype of a GTM agent you would build for Nash. Both are very much encouraged.
Want to grab our attention and bypass the recruiting platform? Record a video introducing yourself at testimonials.nash.ai with code JOIN-NASH. Your application notifies us in Slack the moment it lands, and we get some much needed testing coverage on our latest Claude build :)
More about Nash
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