Nominal builds software that lets hardware teams test, iterate, and deploy as fast as software teams.
The Role
Build and maintain GTM revenue infrastructure: Salesforce data model, data pipelines between sales tools, internal tooling (forecast trackers, comp calculators, dashboards), AI-driven workflows, and code repos. Partner with Sales, Marketing, and CS to improve data quality, automation, and tooling reliability while prototyping new integrations and maintaining governance.
Summary Generated by Built In
About Nominal
Our first GTM Engineer
🚀 About the role
🙌 We'd love to hear from you if
⚡ Skills that supercharge us
✨ Benefits/Perks
Compensation
Nominal is building the connected test and operations platform powering the world's most advanced hardware systems, from spacecraft and autonomous vehicles to next-generation defense programs. Our platform gives hardware engineering teams a single place to ingest data, analyze performance, automate test execution, and collaborate across every phase of development, so they can move faster without sacrificing safety or precision. We're a fast-moving team that owns problems end-to-end, works across disciplines, and thrives at the intersection of hardware and software.
We serve top-tier commercial and defense customers, from autonomy leaders like Anduril and Shield AI to next-generation aerospace teams like Hermeus and REGENT, and performance engineering teams like Pratt Miller Motorsports, alongside mission partners within the U.S. Navy and U.S. Air Force on programs where failure isn’t an option. We’re backed by Sequoia, General Catalyst, Founders Fund, Lux Capital, and Lightspeed. Our team draws from SpaceX, Palantir, Anduril, Applied Intuition, and other leading companies, united by a common mission: giving hardware engineers the tools to build the future with speed, safety, and confidence.
Nominal's revenue organization generates an enormous amount of data across our customers, products, and market. Today, turning that data into action still requires too much manual work and too many disconnected systems.
We're hiring our first GTM Engineer to change that. You'll build the technical infrastructure that helps Nominal identify the right customers, understand when they're ready for us, and turn signals across our market and product into action. That means building data pipelines, internal tools, AI-powered workflows, and systems that connect our GTM stack.
This is an engineering role embedded within Revenue Operations. You'll own problems from idea to production, work directly with GTM leaders and engineers, and have significant freedom in how you solve them.
- Build our GTM data infrastructure. Connect data across Salesforce, Snowflake, Gong, enrichment sources, and external APIs into reliable pipelines and models that the revenue organization can act on.
- Create a signal engine for our market. Develop systems that identify external signals indicating when companies are likely to need Nominal, ingest and structure that information, and turn it into dynamic account scoring and prioritization.
- Build internal products from the ground up. Own tools for territory planning, account intelligence, forecasting, reporting, and other workflows from initial problem through deployment and iteration.
- Use AI as a core development tool and product primitive. Build agents and automated workflows that transform unstructured information, surface insights, enrich data, and eliminate manual work across the GTM organization.
- Turn product usage into revenue signal. Build pipelines and workflows that identify meaningful changes in customer behavior and make that information actionable for the teams supporting those customers.
- Own what you ship. Maintain the repositories, pipelines, integrations, monitoring, and data quality behind your systems and ensure they remain reliable as Nominal scales.
- Find problems worth solving. Work directly with Sales, Marketing, Customer Success, and Revenue Operations to understand how work happens today, identify opportunities for leverage, and determine what should be automated or rebuilt.
- You have 2–4 years of experience in data engineering, software engineering, analytics engineering, technical revops, or another highly technical role where you built production systems.
- You have strong software engineering fundamentals and can understand, modify, and own the systems you build rather than relying on AI-generated code you can't explain.
- You are comfortable working with SQL and Python and have experience interacting with databases, APIs, and data pipelines.
- You've built systems that move and transform data across multiple sources and can explain the architecture, tradeoffs, and reliability considerations behind them.
- You're highly fluent with modern AI development tools and actively use them to build faster, explore unfamiliar systems, and automate work.
- You have unusually high agency. When you encounter something you don't know, your instinct is to learn it, build it, and figure out how to make it work.
- You communicate clearly with both technical and non-technical partners and can translate an ambiguous business problem into a technical system.
- You're excited by the idea of applying engineering to revenue problems rather than needing everything you build to live inside the core product.
- Experience with Snowflake, Salesforce, or modern data infrastructure.
- Experience building internal tools, analytics products, or data platforms for Sales, Marketing, Growth, or another business function.
- Experience integrating LLMs, agents, or AI workflows into production systems.
- Familiarity with Model Context Protocol (MCP) or similar agent tooling.
- Experience with Gong, Clay, Common Room, or other parts of a modern GTM stack.
- Experience scraping, enriching, modeling, or otherwise turning messy external data into structured information.
- Experience in hardware, aerospace, defense, industrial technology, or another technically complex market.
- 🏥 100% coverage of medical, dental, and vision insurance
- 🏖️ Unlimited PTO and sick leave
- 🍽️ Free lunch, snacks, and coffee
- 🚀 Professional development stipend
- ✈️ Annual company retreat
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.
ITAR Requirements
To conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder), (iii) Refugee under 8 U.S.C. § 1157, or (iv) Asylee under 8 U.S.C. § 1158, or be eligible to obtain the required authorizations from the U.S. Department of State.
Compensation
The base pay range for this role is $110,000 – $180,000 per year.
Skills Required
- 2+ years in an analytical, data engineering, or software engineering role
- Write SQL to build and maintain data pipelines and queries
- At least one scripting language for building tools (Python preferred)
- Fluent with AI tooling and experience applying LLMs in workflows
- Built end-to-end data pipelines (inputs, transformations, outputs) and monitoring
- Ability to take scoped problems to working tools and ask clarifying questions
- Ability to quantify impact in revenue terms (pipeline influenced, hours removed, etc.)
- Maintain data governance, quality, and sync integrity across fast-moving systems
- Design usable internal interfaces without a dedicated designer
- Experience with Gong, Common Room, Clay, or comparable GTM stack tools
- Experience integrating LLMs into GTM workflows (enrichment, scoring, outreach, agentic systems)
- Familiarity with Model Context Protocol or similar agent frameworks
- Experience selling into or supporting technical, hardware, or government/defense buyers
- Portfolio or public examples of shipped systems and results
- ITAR eligibility: must be a U.S. citizen, lawful permanent resident, refugee, or asylee, or be eligible for required State Department authorizations
Nominal Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Nominal and has not been reviewed or approved by Nominal.
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Healthcare Strength — 100% employer-paid medical, dental, and vision coverage is repeatedly described as covering both employees and dependents, indicating unusually strong healthcare provisioning. Additional mentions of “Platinum” coverage reinforce the sense of a high-tier plan offering.
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Leave & Time Off Breadth — Unlimited PTO and paid holidays/sick time are presented as part of the core package, suggesting broad time-off benefits on paper. Parental leave is also framed as fully paid in several places, reinforcing overall leave breadth.
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Wellbeing & Lifestyle Benefits — Wellness stipends, daily gourmet lunch (and sometimes dinner), and periodic retreats are consistently highlighted as meaningful lifestyle perks. Learning/development and other small stipends further round out a perks-heavy total rewards posture.
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The Company
What We Do
Nominal builds the essential software stack that enables hardware teams to test and iterate as rapidly as software teams. Nominal empowers engineers to continuously monitor, validate, and deploy innovations, transforming how mission-critical hardware is built and operated.
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