Staff Software Engineer, GTM Systems

Job summary

ABOUT Ant*** Ant***’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

Benefits

Qualifications

• Have strong software engineering fundamentals: version control discipline, testing, code review, deployment automation, and a bias toward simple designs
• Have built the delivery pipeline for a team, not just worked within one, and can describe the sequencing choices you made
• Have led a team through a step change in engineering practice as its scope grew, including what you did when adoption slowed
• Work fluently with AI coding
• Have worked on business-critical enterprise platforms where financial correctness and auditability mattered
• Have experience with Salesforce or comparable enterprise platforms, including their metadata and deployment models
• Have built tooling or agents on top of an enterprise system of record
• Have operated in a company under audit or compliance constraints
• The annual compensation range for this role is listed below.
• For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
• Annual Salary:
• 320,000 - $405,000 USD

Responsibilities

• Lead architecture reviews for GTM systems that process lead-to-cash transactions and generate the data points the organization runs on, including changes originating in other teams that land on our platform
• Architect and mature the engineering pipeline the team develops against: pull request workflow, CI/CD, automated UAT, and the deploy path from source control to production
• Establish shared AI-assisted development standards for the team, converting existing individual usage into consistent practice that holds up under review
• Work with engineering teams outside GTM on shared architectural problems and common tooling, where the right answer is a platform decision rather than a local one
• Build and shape the agentic tooling running on top of our platform, and set the pattern other engineers follow when they build the next one
• Trace the dependency chain from upstream data and downstream quoting and provisioning systems, and make sure design decisions account for what they break
• Partner with the platform developers on the team as engineering practice deepens, expanding what the team can safely ship
• MINIMUM

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