GTM Engineer
New
P
PragmatikeAI data infrastructure
Location: United States; Secondary Locations: Colombia, Sacramento, Los Angeles, San Francisco, Canada, Costa Rica, Mexico; Workplace: Remote; Fully Remote (Pacific time zones), Pacific time zones; working hours aligned with Singapore or US Pacific business hours, depending on location.Full-TimeMiddle
Salary not disclosed
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Job Details
- Languages
- Fluent English required
- Experience
- 2+ years of professional software engineering experience.
- Required Skills
- PythonSQLTypeScriptCRM
Requirements
- Have 2+ years of professional software engineering experience.
- Have strong programming skills in Python or TypeScript.
- Be fluent in SQL.
- Have experience building internal tools, automations, or integrations used by other teams in daily operations.
- Have hands-on experience developing data pipelines and API integrations between business systems.
- Be able to translate business needs into practical technical solutions.
- Bring commercial awareness and interest in revenue operations, including understanding sales workflows and prioritizing projects that support business growth.
- Have clear written communication skills and the ability to take ownership in ambiguous, fast-moving environments.
- Nice to have: experience in RevOps, growth engineering, sales engineering, or forward-deployed engineering.
- Nice to have: hands-on experience implementing LLMs or AI agents in production environments.
- Nice to have: experience at an early-stage startup or as a founder.
- Nice to have: familiarity with AI training data, including RL environments, evaluations, and benchmarks.
Responsibilities
- Own, select, configure, integrate, and maintain the GTM tooling stack.
- Build sourcing systems, including scrapers and data enrichment pipelines, to identify data providers and opportunities.
- Develop and maintain data infrastructure connecting CRM, marketplace, and product data.
- Build internal tools for provider research, listing quality checks, pipeline management, and sales forecasting.
- Automate workflows across sourcing, qualification, lead routing, and reporting.
- Identify operational bottlenecks with founders and the commercial team, and prioritize automation projects.
- Explore and implement AI agents where they offer advantages over traditional automation.
- Make build-versus-buy decisions to keep GTM tooling efficient, reliable, and maintainable.
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