Spend the majority of your time "hands-on-keyboard," architecting and coding high-performance backend services and ML pipelines.
Build and prototype new internal products from scratch that leverage LLMs and Agentic AI to automate account research, lead prioritization, and complex quoting logic.
Design and implement ML models that provide real-time recommendations to sales users, reducing manual entry and increasing deal velocity.
Develop the backend connective tissue between our custom quoting engine, Salesforce, and internal data lakes to ensure a seamless, low-latency end-to-end experience.
Act as a domain expert to solve complex synchronization and architectural challenges across the GTM stack, ensuring systems are scalable and resilient.
Drive engineering excellence through rigorous code reviews, automated testing, and by modeling best practices for SE1-SE3 engineers on the team.
Deliver significant core capabilities that have broad impact; take high-level goals and turn them into sequenced, production-ready code.
Anticipate shifts in product needs and build flexible, decoupled backend systems that can evolve with our AI strategy.
Ensure the reliability of GTM tools by building deep observability into every service you ship.

Extensive experience in backend languages (Java, Go, Python) with a track record of building complex, distributed systems.
Practical, hands-on experience deploying Machine Learning models and building with LLMs (e.g., LangChain, RAG architectures, or Model Fine-tuning) in a production environment.
Experience building or deeply integrating with complex enterprise software, specifically custom quoting engines or CRM internals (Salesforce Apex/LWC).
Ability to design event-driven architectures and manage data flow across disparate systems with high integrity.
Bachelor’s or Master’s degree in Computer Science, or a related technical field.

Principal Software Engineer

Key skills