Applied AI Software Engineer, GTM

Antithesis; San Francisco (CA); On-site; USD 170,000 - 210,000; Full time

Job summary

Antithesis is hiring an Applied AI Software Engineer to build AI-native products that empower go-to-market and marketing teams. You’ll work at the intersection of software engineering, applied AI, data, and GTM operations.

You will design, build, and ship full-stack products using AI to help non-technical teams get work done, with workloads ranging from lightweight agent workflows to production apps for GTM problems.

Qualifications

• 4+ years of professional software engineering experience, shipping and operating production systems.
• Experience shipping an LLM-powered product or workflow for real users.
• Experience working with non-technical users to gather feedback.
• Experience integrating with business systems such as Salesforce, HubSpot, Gong, or Slack.
• Strong product and engineering judgment; balance experimentation with reliability.

Responsibilities

• Work directly with Sales, Marketing and RevOps to understand workflows and where tech can help.
• Design, build, and ship full-stack AI-powered products for non-technical teams.
• Develop agent workflows and production applications for GTM tasks (research, enrichment, account scoring, etc.).
• Make build-versus-buy decisions; reuse tools, create integrations, or build apps.
• Partner with RevOps to integrate with Salesforce, Marketo, Gong and other GTM systems.

Skills

LLM integration

Full-stack

AI-powered product

Sales/Marketing tooling

Tools

TypeScript

React

LangChain

AWS

Job description

About Antithesis

We're on a mission to redefine how modern distributed systems are tested and released. Our platform is trusted by engineering teams who demand rock-solid reliability, scalable performance, and deep technical visibility. Our platform doesn't just assure system correctness and reliability, it exists because developers need something better. If you've ever experienced the pain of a production outage, had a bad week on-call, or had a release delayed by weeks because of one killer bug - you'll understand exactly why we're doing what we do. If you're passionate about developer-first products, system resilience, and correctness, we'd love to talk.

About the Role

We're hiring an Applied AI Software Engineer to build AI-native products to help our go-to-market and marketing teams.

You'll work at the intersection of software engineering, applied AI, data, and GTM operations.

What You'll Do

• Work directly with Sales, Marketing and RevOps to understand how they work, where they get stuck, and how they could do more with technology.

• Design, build, and ship full-stack products that use AI to help non-technical teams get work done.

• Build everything from lightweight agent workflows and automations to production applications for research, enrichment, account scoring, and other GTM problems.

• Make pragmatic build-versus-buy decisions. The right solution might use an existing tool, a reusable agent skill, a custom integration, or a full application.

• Partner with RevOps to integrate with the systems that GTM teams use like Salesforce, Marketo, and Gong.

Why Join Us?

• Join a collaborative, kind team supporting a rapidly-growing sales organization.

• Work with the resources - tools, teammates, and world-class experts - to do portfolio-worthy work.

• Use and explore AI in an environment that does not tolerate workslop.

Preferred Qualifications

• 4+ years of professional software engineering experience, including independently shipping and operating production systems.

• Experience shipping an LLM-powered product, feature, or workflow for real users. You understand the difference between an impressive prototype and a system people can depend on.

• Experience working directly with non-technical users to understand their workflows, test ideas, and improve products through feedback.

• Experience integrating with business systems such as Salesforce, HubSpot, Gong, Slack, or data-enrichment platforms.

• Strong product and engineering judgment. You can move quickly when the problem calls for an experiment and build for reliability when the solution becomes business critical.

Our current stack for internal GTM applications includes TypeScript, React, LangChain, and AWS. Experience with these tools is helpful, but we care more about strong engineering fundamentals and the ability to learn.