Go-to-Market (GTM) Engineer

Job Description

The GTM AI Engineer will play a key role in developing and operationalizing the AI-driven capabilities of our global go-to-market organization. This position combines data engineering, applied machine learning, and business understanding to build AI systems that improve the way we measure, forecast, and manage performance across Sales, Marketing, and Customer Success. Working within a cross-functional GTM performance team, you will design and maintain AI agents, data pipelines, and predictive models that enhance efficiency, provide timely insights, and automate decision support.

This role is Hybrid based on-site three days per week in our Atlanta, GA or Austin, TX office.

AI System Development & Support

Develop, train, and maintain machine learning and AI models that analyze GTM data (e.g., pipeline conversion, forecast accuracy, churn prediction). Build and manage data pipelines and APIs connecting CRM, marketing, and customer systems to analytical and AI platforms. Collaborate with senior data engineers and analysts to ensure reliable, secure, and high-quality data flows.

Automation & Intelligent Insights

Support the creation of AI agents and workflows that monitor KPIs, detect anomalies, and deliver recommendations to GTM teams. Contribute to automation of recurring performance analyses and forecasting tasks using AI tools and scripting. Assist in integrating AI outputs into dashboards and business systems (Salesforce, Power BI, Adaptive Insights).

AI Training and Testing

Prepare and document training datasets, prompts, and evaluation metrics for AI models. Participate in model testing, validation, and continuous improvement cycles.

Collaboration & Continuous Learning

Partner closely with GTM operations, analytics, and data science teams to translate business problems into AI use cases. Stay current with emerging AI/ML tools, frameworks, and best practices to drive innovation and efficiency. Communicate results and model insights clearly to both technical and non-technical stakeholders.

Qualifications

4+ years of experience in AI engineering, data science, analytics, or software engineering Ideally with 1+ year of GTM engineering at a SaaS company. Strong technical skills in Python, data wrangling, and machine learning frameworks Exposure to LLM or generative-AI frameworks a plus. Familiarity with SQL and data platforms Understanding of B2B GTM or revenue data preferred. Strong analytical and problem-solving abilities, with attention to accuracy and data integrity. Excellent communication and collaboration skills; able to work effectively with cross-functional teams. Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related discipline.

Plenty of perks:

Competitive salaries that landed us top 5% of similar sized companies (according to Comparably) Comprehensive health, dental and vision coverage 401(k) retirement match (100% matching up to 4%) 32 days paid time off (21 personal days, 10 national holidays, 1 floating holiday) 18 weeks paid parental leave for birth, adoption or surrogacy offered 1 year after start date 5 days paid yearly to volunteer (through Sage Foundation) $5,250 tuition reimbursement per calendar year starting 6 months after hire date Sage Wellness Rewards Program ($600 wellness credit and $360 fitness reimbursement annually) Library of on-demand career development options and ongoing training offerings

What it’s like to work at Sage:

Careers homepage - https://www.sage.com/en-us/company/careers/

Glassdoor reviews - https://www.glassdoor.com/Reviews/Sage-Reviews-E1150.htm

LinkedIn page - https://www.linkedin.com/company/sage-software