GTM Engineer
Together AI is hiring a GTM Engineer in San Francisco, United States. It pays $160k-$190k a year and Level rates it ; you can apply on Together AI.
Level's read on this job
- Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include Claude, Cursor and Elevenlabs.
- Level classifies it as a senior role.
- Level lists 83 other open roles at Together AI.
AI in this role
Architect an AI-native go-to-market tech stack and build automated data pipelines and AI agents.
About the Role
We are seeking a skilled GTM Engineer to join our team. In this role, you will architect an AI-native tech stack with seamless integrations and build a cohesive, automated engine to drive measurable revenue outcomes. As a builder and systems thinker, you will play a vital role in automating processes, maintaining data integrity, and turning GTM strategy into scalable systems.
Responsibilities
- Architect the GTM Tech Stack: Build an AI native tech stack with seamless integrations.
- Centralize Data: Build a cohesive, automated engine that centralizes data in CRM and eventually data warehouse (Salesforce, Hubspot, Snowflake, Clay, Claude Cowork).
- Own Data Integrity: Build and maintain the data flows, enrichment logic, and sync architecture that keep our systems accurate, deduped, and trustworthy end-to-end.
- Turn Strategy into Systems: Partner with leadership to translate GTM strategy into automated playbooks, dynamic scoring models, and signal-based workflows that drive measurable revenue outcomes.
- Lead CPQ System Design: Lead system design for Salesforce CPQ, including product catalog architecture, pricing and discount rules, quote templates, and approval workflows.
- Optimize Conversions: Optimize quote-to-order conversion ensuring accurate data flow into downstream billing and ERP systems.
- Implement Governance: Implement governance on pricing, discounting, and quote approval thresholds to maintain margin and compliance integrity.
- Improve Deal Velocity: Improve deal velocity by streamlining approvals, leveraging Salesforce CPQ (Revenue Cloud).
- Integrate CLM Tools: Integrate CLM (e.g., Ironclad, Conga, or DocuSign CLM) with Salesforce to automate quote-to-contract and contract-to-order workflows.
- Automate Bottlenecks: Identify repetitive work across the GTM org - account research, CRM hygiene, post-call follow-ups - and replace it with intelligent automation using APIs, webhooks, and AI agents.
Requirements
- Experience: Have 3–5+ years of experience operating in a Growth, GTM Engineer, or Revenue Operations role. Open to candidates that have a technical background that have worked with a GTM team in other capacities.
- Systems Thinking: Are a builder and systems thinker: You want to build moonshot ideas, not just toggle settings. You see the GTM stack as an interconnected machine, not a collection of point solutions.
- Salesforce Expertise: Have Direct experience with Salesforce — you know the data model, you've built on it, and you're comfortable owning CRM-level changes.
- GTM Fluency: Are GTM-fluent: You understand the GTM funnel - not just the data model, but the logic behind every stage. You know what actually converts pipeline because you've worked in or alongside GTM teams.
- Quote to Cash Configurations: Strong working knowledge of quoting tool configurations and CLM (pricing rules, product bundles, approval chains).
- Execution & Ownership: Constant iteration: Be a Kaizen methodology champion by building, shipping and iterating fast. You thrive in ambiguity, operate with high ownership, and move fast without waiting for perfect requirements. But you know when to slow down and ensure you’re shipping the highest quality work possible.
- Technical Capability: Are technically capable: Comfortable working with APIs, webhooks, data integrations and can navigate technical documentation without hand-holding.
Preferred Qualifications
- Prior experience at a fast-moving B2B SaaS / AI startup or strong familiarity with the AI tooling ecosystem.
- Hands-on experience with Salesforce and Clay, bonus points for building data warehouses.
- Prior quoting tool and CLM implementation experience.
- Experience designing enrichment and outbounding process and managing complex data sourcing across multiple providers.
- Experience centralizing selling signals from multiple data sources into a single location.
- You have technical familiarity with GTM & automation tools (Salesforce, HubSpot, CPQ, Ironclad, Clay, Gong, Apollo, Clari, APIs, webhooks, etc.).
As our ideal candidate, you will be part engineer, part hacker, with a passion for cybersecurity and a drive to protect our systems from evolving threats.
About Together AI
Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month.
Compensation
We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160K-190K + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.
Equal Opportunity
Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.
Please see our privacy policy at https://www.together.ai/privacy.
How we rate this
GTM Engineer at Together AI rates 60 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- Tell me about a workflow you automated with AI tools, end to end.
- Tell me about a project where revenue operations was part of your work. What did you do?
- Tell me about a project where system integration was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, Fine-tuning, AI Automation, Revenue Operations, and System Integration. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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