Build and ship production AI features that deliver measurable customer value.
Work directly with customer teams to understand workflows, pain points, and success criteria.
Design and implement end-to-end solutions using Python and production LLM systems.
Translate customer requirements into reusable product capabilities, not one-off custom work.
Partner closely with Product, Research, and Engineering to prioritize and deliver high-impact features.
Identify repeatable implementation patterns and codify them into internal playbooks.
Travel to customer sites as needed (estimated around 10%) to accelerate deployment and adoption.
Bachelors degree or equivalent practical experience in software engineering, applied AI, or a related technical domain.
Strong Python proficiency and experience shipping production-grade software.
Experience with agentic systems, tool use, and workflow orchestration.
Hands-on experience building and operating production LLM applications.
Experience in customer discovery and translating business requirements into technical solutions.
Strong problem-solving and communication skills across technical and non-technical audiences.
High ownership mindset and ability to execute in ambiguous, cross-functional environments.
Ability to travel to customer sites.
Familiarity with model evaluation, quality measurement, and reliability practices.
Background in forward deployed engineering, solutions engineering, or professional services.
You have built side projects or products that solve real-world workflow problems.
Based on 405 disclosed Sales Engineering salaries on RoleSuite, the role pays a median of $166K/year, with most offers between $134K and $201K (10th–90th percentile: $105K–$250K).
See the full Sales Engineering salary breakdown →