GTM Engineer

Immuta is the Data Provisioning Company, helping organizations provision secure, governed data access at the speed modern business demands. We automate access by policy and by request—eliminating tickets, reducing risk, and enabling both humans and AI systems to work with data safely and instantly.

Founded in 2015, Immuta is trusted by Fortune 500 companies and government agencies worldwide and operates as a hybrid workplace globally.

• Technology partners include Snowflake, Databricks, AWS, Azure, Google Cloud, and Starburst.

• Immuta has been recognized by Forbes as a top American startup employer, by Inc. Magazine and BuiltIn as one of the best workplaces, and by Fast Company as one of the top 50 most innovative companies.

• $267 million in total funding. Lead investors include NightDragon, Snowflake, and Databricks, along with additional funding from ServiceNow, Citi Ventures, Dell Technologies Capital, DFJ Growth, IAG, Intel Capital, March Capital, Okta Ventures, StepStone, Ten Eleven Ventures, and Wipro Ventures.

• A hybrid workplace with offices in Boston, MA; Columbus, Ohio; College Park, Maryland.

ABOUT THE ROLE

• Build and maintain ICP scoring models, intent signal pipelines, and account prioritization logic sourced across our stack (Salesforce, Apollo, Warmly, Clay, and more)
• Own the data transformation layer: pulling from CRM, enrichment APIs, and intent platforms, normalizing and enriching, and writing clean outputs back to Salesforce or downstream activation tools
• Partner with RevOps on data definitions and quality to ensure scoring logic runs on trustworthy inputs
AI-Assisted GTM Workflows
• Apply LLMs to automate research, contact enrichment, signal extraction, and outreach personalization at scale
• Design workflows that are measurable, testable, and repeatable — not one-off prompts
• Reduce manual effort across Sales and Marketing by replacing high-frequency, low-complexity tasks with reliable automation
Middleware & Integration Infrastructure
• Build lightweight orchestration systems that connect GTM tools across the stack
• Own the full lifecycle: standing up, maintaining, and iterating on integrations as the tool stack evolves
• Know when to use n8n vs a custom FastAPI endpoint vs a scheduled Python job, and implement whichever is right
Experimentation & Measurement
• Build the scaffolding that lets the team run GTM experiments across audiences, channels, and messaging
• Instrument experiments with enough signals to distinguish what's working from what's noise
• Operationalize successful approaches by moving from one-off test to repeatable, scalable system