{"id":197525,"url":"https://alion.io/job/antithesis-applied-ai-software-engineer-gtm","title":"Applied AI Software Engineer","company":{"id":7620,"name":"Antithesis","domain":"antithesis.com","url":"https://alion.io/company/antithesis","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":79,"open_postings":8,"ghost_share":0,"stale_share":0.625,"repost_share":0,"time_to_fill_p50_days":77,"computed_at":"2026-11-09T06:03:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Vienna, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":155000,"max":185000,"currency":"USD","period":"year","gross":null,"usd_annual":185000},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":true},{"name":"LangChain","optional":true},{"name":"LLM","optional":true},{"name":"Slack","optional":true},{"name":"TypeScript","optional":true}],"status":"live","first_seen_at":"2026-09-03T14:54:24Z","employer_posted_date":"2026-09-24","last_verified_at":"2026-11-09T05:42:54Z","board_verified":true,"closed_at":null,"days_open":66,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":66},"description":"About Antithesis\nWe’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.\nAbout the Role\nWe’re hiring an Applied AI Software Engineer to build AI-native products to help our go-to-market and marketing teams.\nYou’ll work at the intersection of software engineering, applied AI, data, and GTM operations.\nWhat You’ll Do\nWork directly with Sales, Marketing and RevOps to understand how they work, where they get stuck, and how they could do more with technology.\n\nDesign, build, and ship full-stack products that use AI to help non-technical teams get work done.\n\nBuild everything from lightweight agent workflows and automations to production applications for research, enrichment, account scoring, and other GTM problems.\n\nMake pragmatic build-versus-buy decisions. The right solution might use an existing tool, a reusable agent skill, a custom integration, or a full application.\n\nPartner with RevOps to integrate with the systems that GTM teams use like Salesforce, Marketo, and Gong.\n\nWhy Join Us?\nJoin a collaborative, kind team supporting a rapidly-growing sales organization.\n\nWork with the resources - tools, teammates, and world-class experts - to do portfolio-worthy work.\n\nUse and explore AI in an environment that does not tolerate workslop.\n\nPreferred Qualifications\n4+ years of professional software engineering experience, including independently shipping and operating production systems.\n\nExperience 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.\n\nExperience working directly with non-technical users to understand their workflows, test ideas, and improve products through feedback.\n\nExperience integrating with business systems such as Salesforce, HubSpot, Gong, Slack, or data-enrichment platforms.\n\nStrong 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.\n\nOur current stack for internal GTM applications includes TypeScript, React, LangChain, and AWS. 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