Staff Software Engineer, AI & Strategy

A day in the life (Responsibilities)

• Hands-on Execution: Spend the majority of your time "hands-on-keyboard," architecting and coding high-performance backend services and ML pipelines.
• 0-to-1 Development: Build and prototype new internal products from scratch that leverage LLMs and Agentic AI to automate account research, lead prioritization, and complex quoting logic.
• Core Intelligence Models: Design and implement ML models that provide real-time recommendations to sales users, reducing manual entry and increasing deal velocity.
• Infrastructure Integration: 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.
• Technical Problem Solving: Act as a domain expert to solve complex synchronization and architectural challenges across the GTM stack, ensuring systems are scalable and resilient.
• Quality & Mentorship: Drive engineering excellence through rigorous code reviews, automated testing, and by modeling best practices for SE1-SE3 engineers on the team.
• Build Great Products: Deliver significant core capabilities that have broad impact; take high-level goals and turn them into sequenced, production-ready code.
• Problem Solve: Anticipate shifts in product needs and build flexible, decoupled backend systems that can evolve with our AI strategy.
• Deliver Quality: Ensure the reliability of GTM tools by building deep observability into every service you ship.

What you'll need to thrive (Requirements)

• Deep Backend Expertise: Extensive experience in backend languages (Java, Go, Python) with a track record of building complex, distributed systems.
• Applied AI/ML Skills: 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.
• Technical Complexity: Experience building or deeply integrating with complex enterprise software, specifically custom quoting engines or CRM internals (Salesforce Apex/LWC).
• Systems Architecture: Ability to design event-driven architectures and manage data flow across disparate systems with high integrity.
• Education: Bachelor’s or Master’s degree in Computer Science, or a related technical field.

What will help you stand out (Nonessential Skills/Nice to Haves)

• Experience building internal "Sales Tech" or "Fintech" tools that directly impact revenue.
• Familiarity with AWS data services (SageMaker, Lambda, SQS).
• A passion for removing "human-in-the-loop" friction through intelligent automation.