---
title: 'GTM Engineer - Data Platform at Modal'
canonical: 'https://feeny.ai/job/gtm-engineer-data-platform-modal-new-york-kjkbrxkqfe7z'
type: 'job'
last_seen: '2026-11-03'
---

# GTM Engineer - Data Platform at Modal

- **Company:** Modal
- **Location:** New York, NY
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-10-13
- **Last confirmed live:** 2026-11-03
- **Apply:** https://jobs.ashbyhq.com/modal/dd6fe63b-8265-474e-b1f0-fcc1c5a28daf

## Job description

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.

Our customers include category-defining companies like [Ramp](https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal), Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.

We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation.

Our team includes creators of popular open-source projects (e.g.,[Seaborn](https://github.com/mwaskom/seaborn),[Luigi](https://github.com/spotify/luigi)), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.

About GTM Engineering: GTM Engineering is responsible for the data, business logic, workflows, and agents that enable our Marketing and Sales teams to help customers get the most out of Modal. Like the [infrastructure beneath the Magic Kingdom](https://en.wikipedia.org/wiki/Disney_utilidor_system), much of our work happens behind the scenes. We build systems that anticipate and deliver what customers need to grow on Modal. We bring a product management, growth engineering, and data science approach to GTM, from [centralizing our data platform](https://deepline.com/blog/gtm-ai-nyc-chris-modal) to [building agents for account research](https://parallel.ai/blog/case-study-modal).

The Role: We’re looking for a GTM Engineer to own our GTM data platform. This role combines analytics engineering with revenue operations: you’ll build the org map, people graph, and data systems that help us discover future customers and support our GTM workflows, partnering closely with our Data team on the shared foundation.

What You’ll Work On:

- Build and maintain an org map and people graph connecting companies, labs, teams, and individuals to identify researchers, engineers, and early-stage startups, including people beyond our existing users and CRM
- Own identity resolution, enrichment, and CRM schemas so affiliations, roles, and relationships stay accurate, current, and traceable to their sources
- Build GTM data models in Snowflake and dbt connecting people, companies, workspaces, workloads, usage, and revenue, giving reps and agents a shared foundation for customer context
- Partner with RevOps and Marketing to define and implement metrics, data models, and business rules for routing, territory assignments, compensation, pipeline reporting, and attribution
- Partner with Data on usage forecasts and account signals; build reproducible reporting that reconciles actuals, forecasts, human adjustments, and credited attainment
- Build reverse ETL pipelines for ad audiences, lifecycle campaigns, CRM enrichment, outbound, and event outreach, preserving engagement history and campaign eligibility
- Own data quality and system health, from graph coverage and stale enrichment to failed syncs and historical reporting accuracy
- Build the tooling that helps GTM Engineering ship reliably, from development environments, automated tests, and deployments to backups and shared AI agents and skills

You May Be a Fit If:

- You’re fluent in SQL and proficient in Python
- You already use AI coding tools and agents to build, debug, and automate your work, and help teammates do the same
- You’ve built data models and production pipelines with tools like Snowflake, dbt, Modal, or Hex
- You have hands-on experience with CRM architecture, integrations, and revenue or marketing operations
- You understand how leads, accounts, opportunities, and revenue move through a business
- You have high attention to detail and a habit of testing, documenting, and monitoring the systems you build

Nice-to-Have:

- Experience with usage-based businesses

## About Modal

## Company Overview
- **One-liner**: Modal provides high-performance AI infrastructure—a serverless, globally distributed GPU cloud for inference, training, sandboxes, and agent workloads.
- **Entity Type**: Private (raised over $466M, Series D from top-tier investors)
- **Headquarters**: New York, NY, USA (with offices in Stockholm, Sweden and San Francisco, CA, USA)
- **Founded**: Not publicly available in provided sources
- **Founders**: Erik Bernhardsson and Akshat Bubna

## Core Business
- Primary industry: Cloud infrastructure / AI compute / Developer tools
- Target customers: Developers and engineering teams building AI/ML products (B2B, from startups to enterprises)
- Mission or purpose: “Make it easier to iterate and ship applications for data, AI, and machine learning” and “Make cloud development work like magic.”

## Products & Services
- **[Modal Runtime](https://modal.com/)** – Serverless container platform with custom file system, scheduler, and container image builder. Sub-second cold starts and instant autoscaling from 0 to 1000+ GPUs.
- **[Modal Sandboxes](https://modal.com/)** – Isolated, ephemeral environments for running untrusted code (e.g., coding agents, RL rollouts). Programmatically spin up fresh environments with custom images.
- **[Modal Inference](https://modal.com/)** – Globally distributed inference with sub-10ms overhead latency, support for token streaming, WebRTC, WebSocket. Supports LLMs, audio, image/video generation.
- **[Modal Training](https://modal.com/)** – Fine-tuning and multi-node training on H100s, A100s, B200s with gang scheduling and InfiniBand networking. Single line of code to scale from single-GPU to multi-node clusters.
- **[Modal Batch / Async Inference](https://modal.com/)** – Run evaluations, embeddings, re-ranking, dataset generation at scale, thousands of GPUs fully parallel.
- **[Modal SDK](https://modal.com/)** – Python SDK that lets developers define infrastructure and workloads in code, then ship to the cloud.

## Market Standing
- **Valuation**: $4.65B (as of 2026, per [jobsbyculture.com](https://jobsbyculture.com/blog/working-at-modal-2026))
- **Key Metric**: Total funding raised – over $466M (per [modal.com/company](https://modal.com/company))
- **Notable Investors/Partners**: General Catalyst, Redpoint Ventures, Lux Capital, Amplify Partners, Creandum (per [modal.com/company](https://modal.com/company))
- **Growth Signals**: ~150 employees (2026); global offices in New York, Stockholm, San Francisco; rapid hiring across engineering, GTM, and G&A roles; strong traction in inference, training, and agent infrastructure.

## Competitive Advantages
- **Deep infrastructure stack**: Custom file system, container runtime, scheduler, and image builder built from scratch to optimize AI workloads.
- **Developer experience**: “Stay in Python, ship to the cloud” – composable primitives that specify everything from logic to hardware in one code file.
- **Instant elasticity**: Scale from zero to 1000+ GPUs in seconds, pay only for compute used (no reserved capacity).
- **Global GPU access with low latency**: Sub-10ms overhead for online inference via globally distributed compute.
- **Compliance and security**: SOC 2 and HIPAA compliant, data residency controls, battle-tested isolation for untrusted code.

## Strategic Focus
- **AI-native runtime**: Deepening support for inference, fine-tuning, reinforcement learning, and agent workflows.
- **Scaling for agents**: Developing sandboxes and execution layers purpose‑built for interactive coding agents and long‑running RL rollouts.
- **Expanding global capacity**: Adding GPU availability across more regions, leveraging elastic cloud capacity.
- **Enterprise readiness**: Investing in security, governance, team controls, and data residency to serve larger customers.

## Why Work Here
- **Culture and team**: Founded by engineers who created open‑source tools (Seaborn, Luigi); team includes academic researchers, olympiad medalists, and experienced engineering leaders. Flat, high‑trust environment.
- **Location / flexibility**: Offices in New York, Stockholm, and San Francisco; likely hybrid/remote‑friendly (many roles list multiple locations).
- **Compensation and growth**: Transparent salary culture (as highlighted in 2026 profile); strong growth trajectory backed by $466M in funding and a $4.65B valuation.
- **Perks**: $30/month free compute for personal projects (customer benefit, likely similar for employees); focus on developer experience and “magic.”

## Sources
1. [modal.com](https://modal.com/)
2. [modal.com/company](https://modal.com/company)
3. [jobs.ashbyhq.com/modal](https://jobs.ashbyhq.com/modal)
4. [linkedin.com/company/modal-labs](https://www.linkedin.com/company/modal-labs)
5. [jobsbyculture.com/blog/working-at-modal-2026](https://jobsbyculture.com/blog/working-at-modal-2026)

## Other roles at Modal

- [Talent Partner, Technical](https://feeny.ai/job/talent-partner-technical-modal-new-york-9gqq77qqdag1) — New York, NY
- [Head of IT](https://feeny.ai/job/head-of-it-modal-new-york-a8w16t8ptzer) — New York, NY
- [Member of Technical Staff - Storage (Stockholm)](https://feeny.ai/job/member-of-technical-staff-storage-stockholm-modal-stockholm-24yjjh3wj6n2) — Stockholm, Sweden
- [Member of Technical Staff - SDK (Stockholm)](https://feeny.ai/job/member-of-technical-staff-sdk-stockholm-modal-stockholm-ks7rt2xw6atf) — Stockholm, Sweden
- [Talent Partner, GTM](https://feeny.ai/job/talent-partner-gtm-modal-san-francisco-1nm18692f4w7) — San Francisco, CA
- [Member of Technical Staff - Inference Runtime](https://feeny.ai/job/member-of-technical-staff-inference-runtime-modal-san-francisco-cvzk20vkphfy) — San Francisco, CA
- [Legal Operations Lead](https://feeny.ai/job/legal-operations-lead-modal-new-york-s5y3gn1e961k) — New York, NY
- [Senior Commercial Counsel](https://feeny.ai/job/senior-commercial-counsel-modal-new-york-grh0fxqa82by) — New York, NY
- [Field Marketing Manager](https://feeny.ai/job/field-marketing-manager-modal-san-francisco-0apep5s9tyq6) — San Francisco, CA
- [Global Workplace Lead](https://feeny.ai/job/global-workplace-lead-modal-new-york-4vjzkq1xtb4h) — New York, NY