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GTM AI Engineering

Published · Updated

$160,000–$240,000San Francisco, CAOn-site

Build and own production software, AI agents, and data infrastructure for the company’s internal go-to-market engine.

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View posting at Applied Compute

At a glance

Posted base pay

$160K–$240KAbove the median

The work

Builds for teams inside the company

Balance

  1. Mostly building
  2. Mixed
  3. Mostly pre-sales or support

Project stages

  1. Pre-sales (not covered)
  2. Proof of concept (not covered)
  3. Implementation
  4. Operations
Coding
Writes production code
Builds for
Internal teams
Level
Senior
Role
Individual contributor

What they ask for

Tools

  • Python
  • TypeScript
  • SQL
  • LLMs
  • agent workflows
  • automated testing
  • CRM integrations

Visa

  • Sponsors visas

Less common in FDE jobs

  • Company size: About 1–50 people13%
  • Who you build for: Internal teams14%
  • Company stage: Early17%
  • Sponsors visas22%

Share of US FDE postings that state each fact.

The job description from Applied Compute

Posted by Applied Compute on

As a GTM AI Engineer at Applied Compute, you’ll build the software, agents, and data infrastructure that power our go-to-market engine. Your systems will help us identify promising accounts, reach the right people, and turn information from across our business into actionable insights.

This is a software engineering role dedicated to our internal GTM systems. You’ll spend your time designing, coding, deploying, and improving tools our team uses every day. You’ll own projects from problem definition through production, with responsibility for their architecture, reliability, and business impact.

You’ll work closely with our GTM team to understand their workflows, prioritize what to build, and improve the systems as the company grows.

What you’ll do

  • Build agents and applications for GTM workflows. Develop systems for account research, prospect discovery, outreach personalization, inbound qualification, and pipeline reporting.
  • Build the data foundation. Connect our CRM, communication tools, meeting transcripts, and external data sources. Make account and contact information accurate, current, and accessible to the people and agents that need it.
  • Turn recurring work into reusable software. Identify manual bottlenecks and build tools that reduce repetitive work and help the team act on relevant information.
  • Make LLM workflows reliable. Develop evaluations, review workflows, and feedback loops that improve research accuracy, generated content, and agent behavior.
  • Own production quality. Maintain a shared codebase with code review, automated testing, monitoring, documentation, and reliable deployments. Debug failures and improve systems as usage grows.
  • Measure and improve results. Instrument workflows to understand their effect on qualified pipeline, conversion, and time saved. Use those results to guide experiments and engineering priorities.

What we’re looking for

  • Prior professional experience as a software engineer or machine learning engineer, building and maintaining production systems on an engineering team.
  • Strong programming skills in Python or TypeScript, with experience working with APIs, databases, and integrations.
  • Hands-on experience building with LLMs, including tool use, agent workflows, and evaluations.
  • Comfort working with SQL and messy data, including reconciling information across multiple sources.
  • Strong engineering judgment: you can ship quickly while keeping systems understandable, testable, and maintainable.
  • Ownership and product sense. You can turn an ambiguous business problem into a useful tool, work directly with its users, and improve it based on evidence.

Nice to have

  • Experience building internal tools, data pipelines, or automation used by a sales, marketing, or growth team.
  • Familiarity with CRM systems, enrichment providers, and sales engagement tools.
  • Experience designing experiments and measuring how software changes affect business outcomes.

The U.S. base salary range for this full-time position is $160,000–$240,000. Total compensation for this role also includes meaningful equity in a fast-growing startup, along with a comprehensive benefits package designed to support you both personally and professionally. Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location. The listed salary range is intended as a guideline and may be adjusted.

Benefits & Logistics

This role is based in San Francisco. We work from our office in the Mission. We offer:

  • Competitive compensation and equity
  • 100% employer-paid health insurance coverage for you and your family
  • Unlimited PTO
  • Paid parental leave
  • Daily lunches and dinners
  • Transportation and relocation support
  • 5% 401(k) match

We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the process with you. We encourage you to apply even if you do not believe you meet every single qualification. As set forth in Applied Compute’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

View posting at Applied Compute

About Applied Compute

Builds 'specific intelligence' AI agents trained from scratch on each enterprise customer's own data, sold to companies like DoorDash, Mercor, and Cognition.

Series A · 10–50 people

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Pay and conditions

Posted pay
$160,000–$240,000
Pay details

The U.S. base salary range for this full-time position is $160,000–$240,000. Total compensation for this role also includes meaningful equity in a fast-growing startup, along with a comprehensive benefits package designed to support you both personally and professionally. Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location. The listed salary range is intended as a guideline and may be adjusted.

Location
San Francisco, CA
Work arrangement
On-site
Employment type
Full-time
Visa sponsorship
Available