Founding Forward Deployed Engineer

Inventure; New York (NY); On-site; USD 180,000 - 250,000; Full time

Job summary

Inventure is seeking a Founding Forward Deployed Engineer in New York City (onsite) to bridge customer data with production-ready agent workflows and drive real revenue outcomes. This early-stage role blends deep data work with customer engagement across two to three accounts, aligning business concepts with verified data models.

You’ll join a startup backed by notable investors and work on AI-native platform deployments for Fortune 500 clients, including onboarding and servicing engagements

Qualifications

• 2–5 years in forward deployed engineering, data science or customer-facing software engineering with end-to-end deployments.
• Proven production data pipelines or systems delivery without hand-holding.
• Deep SQL and data-warehouse fluency, able to map undocumented schemas to business concepts.

Responsibilities

• Onboard new customers end to end: scope data access, explore undocumented warehouses, and map chaotic schemas onto business concepts like churn, expansion and ARR.
• Build and validate the semantic and ontology layer; interview stakeholders and encode definitions into verified SQL.
• Deploy platform workflows and agent pipelines into customer instances and monitor for measurable revenue.
• Manage two to three concurrent customer engagements, collaborating with customer data and engineering teams.
• Contribute feedback on eval guardrails, validation frameworks and agent harness to improve tooling.

Skills

SQL

Data Warehousing

Stakeholder Management

Python

dbt

AI tooling

Education

BS in CS/Data Science/Statistics

Tools

Claude

Cursor

dbt

Job description

Founding Forward Deployed Engineer | Backed by TQ Ventures and HubSpot, already live with Fortune 500 customers | New York (Onsite) | $180K–$250K base

We’ve partnered with an AI-native startup going after one of the biggest untapped gaps in enterprise software: post-sales. The whole industry has been built to win customers; almost nobody has built to grow them after the sale, and that’s where the margin and the long-term value actually sit. Their platform combines LLMs with structured customer data to automate account scoring, segmentation and expansion playbooks, in effect building autonomous revenue teams for B2B enterprises. This isn’t a pre-revenue bet: they’re already live with Fortune 500 customers including ServiceNow and have gone from zero to $1M in contracts. They’ve raised $11M from TQ Ventures, a $2B+ multistage fund, and HubSpot Ventures, and it’s a tight founding team in New York.

This is the founding engineering seat that gates every customer deployment, which makes it the highest-leverage technical role at the earliest stage of a category-defining company. You’ll be the bridge between messy customer data warehouses and production-ready agent workflows, translating tribal business knowledge into verified data models that drive real revenue outcomes. One thing to be straight about up front: this is deep data work. Roughly 20 to 30 percent is customer-facing and 70 to 80 percent is heads‑down in the data. If that split sounds like the fun part rather than the grind, you’ll thrive here.

The Role

As a Founding Forward Deployed Engineer, you will:

• Onboard new customers end to end: scope data access, explore undocumented warehouses, and map chaotic schemas onto real business concepts like churn, expansion and ARR.
• Build and validate the semantic and ontology layer, interviewing stakeholders, resolving conflicting business definitions, and encoding them into verified SQL.
• Deploy platform workflows and agent pipelines into customer instances, then monitor them and make sure they deliver measurable revenue.
• Manage two to three concurrent customer engagements, working directly in shared Slack channels with customer data and engineering teams.
• Dogfood the internal agent tooling and feed back to engineering on eval guardrails, validation frameworks and the agent harness itself.

About You

• You have 2 to 5 years as a forward deployed engineer, data scientist or customer‑facing software engineer, and you’ve owned customer deployments end to end: data access, schema mapping, stakeholder management and proving value delivery.
• You’ve shipped production data pipelines or systems independently, writing the code, diagnosing the issues and deploying without hand‑holding.
• You have deep SQL and data‑warehouse fluency, can navigate undocumented legacy schemas and produce validated output on your own, ideally with dbt.
• You’re AI‑native: you use tools like Claude and Cursor daily and have built or customised your own agent‑driven workflows.
• You have applied data‑science literacy (distributions, seasonality, validation design) and can tell when a result is signal and when it’s noise.
• You’re genuinely comfortable that most of this role is detailed, repetitive data verification, and you can hold a technical position under customer pushback, changing your mind for evidence rather than authority.
• One of these backgrounds fits you: an FDE or solutions engineer at a top data and AI company such as Palantir, Databricks, Snowflake or Fivetran; an analytics engineer or data scientist who moved into customer‑facing delivery; or someone from consulting, PE or IB with a real CS and engineering background.
• You have a BS in CS, Data Science, Statistics or a quantitative STEM field, and early‑stage startup experience is a plus.
• You’re based in or willing to relocate to New York City and happy to work on site five days a week in Tribeca. Relocation support is available, and the company is open to visa transfers including OPT and H-1B.