GTM Engineer

About the role

• Sentra is an AI Data Readiness platform for enterprises deploying AI at scale. It continuously discovers, classifies, and governs sensitive data across cloud, SaaS, data warehouses, and AI environments, giving security teams visibility into what AI systems can access and expose, and where compliance violations exist.
• Sentra provisions ephemeral scanners directly inside customers' environments rather than copying data to vendor clouds or requiring customer-managed outpost infrastructure, delivering petabyte-scale classification at a fraction of the cost. Customers include Lyft, SoFi, Munich Re, PennyMac, and Glovo.
• Sentra's revenue infrastructure continuously syncs GTM data into a warehouse. AI pipelines score every open deal daily and write conclusions back to the CRM, while attribution models span a hundred thousand touchpoints. A partner deal-registration portal, content platform, and internal dashboard suite are in production, deployed through CI with automated rollback. These systems were designed and shipped in-house in hours to days rather than weeks.
• As the founding GTM Engineer within the GTM Engineering & RevOps team, you will take ownership of existing production systems, harden them, and extend automation into additional parts of the revenue lifecycle. The GTM team is your user base. You will identify revenue leakage, build systems to close gaps, and own both the commercial reasoning behind deal progression and the AI systems that enable action.
• This is a full-time, on-site role in New York City.

Responsibilities

• Build, enhance, operate, and maintain the revenue data platform, AI automations, and workflows, including CRM-to-warehouse synchronization, enrichment and scoring pipelines, and revenue forecasting systems. Ensure outputs remain reliable and trusted.
• Own revenue lifecycle systems end to end, from first touch, demand capture, and lead flow through pipeline management, forecasting, renewals, and expansion, rather than maintaining disconnected stacks with handoffs.
• Create analytics infrastructure that helps decision-makers scale the business. Keep every published number versioned and supported by a reason.
• Drive adoption by measuring whether representatives use the systems you build. Treat non-adoption as a system defect rather than a failure of the representative.

Requirements

• Experience building pipelines in which an LLM is a component, with informed approaches to verifying its output. The team uses agentic coding tools such as Claude Code, Cursor, or equivalent.
• At least 5 years of experience in GTM operations, sales engineering, revenue operations, marketing operations, or sales systems at a B2B SaaS company, preferably at high-growth startups scaling from $10M to $100M+ ARR.
• Data and Git fluency: independently write joins and window functions for pipeline reporting, recognize incorrect results caused by query errors, and work with branches, pull requests, code review, and conflict resolution. Everything ships through version control and CI.
• Practical scripting and API experience using Python, TypeScript, or JavaScript, including reading API documentation, handling authentication, paginating responses, and managing rate limits independently.
• Deep Salesforce knowledge, including object model design, writing and debugging record-triggered flows, sharing and field-level security, and knowing when a formula field is more appropriate than automation.
• Enterprise marketing automation experience. Marketo is strongly preferred; Pardot, Eloqua, or comparable platforms are considered. Responsibilities include sync behavior, deduplication, and lead-to-contact matching.
• Commercial judgment: explain what a stalled deal looks like in the data and why it matters to a quarter.