Antithesis
Applied AI Software Engineer, GTM
About this role
Antithesis is hiring an Applied AI Software Engineer to develop AI-powered tools that streamline GTM operations for sales, marketing, and RevOps teams. You'll design and ship full-stack products—from agent workflows to production applications—that integrate with platforms like Salesforce and Gong to solve real workflow challenges.
What you'll do
- Collaborate with Sales, Marketing, and RevOps teams to identify pain points and design AI-driven solutions
- Design, build, and deploy full-stack products using LLMs and agent workflows for GTM use cases
- Develop solutions for account scoring, data enrichment, research automation, and other revenue operations problems
- Integrate applications with business systems including Salesforce, Marketo, Gong, and Slack
- Make pragmatic technical decisions balancing custom development, existing tools, and reusable agent skills
- Ship and operate production systems with high reliability standards
What they're looking for
- Full-stack software engineering with 4+ years professional experience
- LLM-powered product development and deployment
- TypeScript and React
- LangChain and prompt engineering
- AWS cloud platform
- API integrations with CRM and business systems
- Workflow automation and agent design
- Product thinking and user feedback incorporation
Benefits
- Collaborative and kind team culture
- Access to world-class tools and expertise
- Opportunity to do portfolio-worthy work with AI
- Direct partnership with growing go-to-market organization
- Rapid growth environment
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Antithesis
Antithesis builds a deterministic simulation platform for distributed systems testing that identifies bugs traditional testing methods miss. The company is hiring software engineers, customer-facing technical roles, and infrastructure specialists to develop its core platform and support customers in discovering and resolving bugs in their systems.
- Website
- antithesis.com
Likely interview questions
- Can you describe a production LLM-powered feature or product you shipped and how you ensured it was reliable for real users?
- How do you approach understanding workflows and pain points when working with non-technical teams, and can you share an example?