Senior Engineering Manager - GTM

Mercury•Portland, OR

7h•$239,000 - $298,800

About The Position

Mercury is building a new go-to-market (GTM) Engineering function to connect customer interactions across marketing, sales, and its product. The Senior Engineering Manager will establish the function within an established product organization, shape its technical direction, and develop early GTM systems into dependable production systems, initially leading a team of 2–3 engineers. The role works closely with Product, Data, Marketing, and Revenue, with an initial focus on connecting product and marketing efforts so the company can monitor performance, understand outcomes, and improve them. This is a hands-on leadership role that involves investigating unfamiliar systems, building and validating early solutions, and helping engineers take ownership as systems mature. The work spans TypeScript and Node.js services, Customer.io, Salesforce, and Snowflake, as well as integrations with Mercury’s core application and Haskell backend.

Requirements

Strong experience in either GTM engineering, including marketing technology, or growth engineering.
Professional engineering management experience, supported by recent hands-on engineering work.
Practical experience using AI to build software or improve workflows, with the judgment to evaluate results and make them dependable.

Nice To Haves

Experience shipping AI-powered GTM workflows is strongly preferred.

Responsibilities

Set the technical strategy for Mercury’s GTM engine, deciding which capabilities to build and how they connect with existing marketing, sales, and data systems.
Build orchestration that turns product launches and ongoing GTM strategies into coordinated workflows, connecting audiences and signals to actions across channels.
Improve technology supporting inbound and outbound sales, including prospect identification, enrichment, qualification, routing, and sales-team actions based on signals.
Build dependable workflows and measurement into delivered systems so the team can identify failures, test approaches, and understand what contributes to acquisition and expansion.
Guide AI capabilities from prototype to dependable use, including evaluation, testing, appropriate human review, and measuring their effect on outcomes.
Lead an initial team of 2–3 engineers while remaining hands-on: investigate systems, build and validate solutions, and help engineers take ownership as solutions grow.
Work closely with Product, Data, Marketing, and Revenue to connect product and marketing efforts.