Staff Software Engineer, EvenUp

• Strong experience building and scaling backend systems, platforms, or infrastructure
• Proven ability to lead complex technical initiatives across teams or domains
• Deep understanding of distributed systems, system design, and technical tradeoff analysis
• High standards for code quality, architecture, and long-term maintainability
• Proficiency in Python, with experience in additional languages such as NodeJS, Go, Java, or C++
• Clear, structured communication and the ability to influence cross-functional stakeholders
• Comfort operating in fast-paced, high-growth, and ambiguous environments
• A strong sense of ownership, accountability, and technical leadership

Desirable

• The AI Platform team is responsible for building the foundational systems that make large language models accessible, reliable, and scalable across EvenUp’s engineering organization
• Sitting at the intersection of backend engineering, ML systems, and platform enablement, this team empowers product and application teams to safely and efficiently leverage LLMs in production
• The team has already built and deployed industry-leading legal AI models that extract, structure, and summarize complex documents used by clients every day
• Their work directly powers EvenUp’s ability to deliver faster, higher-quality outcomes for injury victims—bringing greater fairness, accessibility, and leverage to an otherwise opaque legal system
• What makes this team unique is its deeply technical, multi-disciplinary collaboration between Data Scientists, ML Researchers, and Software Engineers, all working together to bring AI systems into production at scale
• The team is focused on building reliable, production-grade AI platforms—not one-off experiments—ensuring that LLM-powered systems are robust, scalable, and safe to operate
• By creating shared infrastructure and tooling, the AI Platform team has a high-leverage impact across the entire engineering organization, enabling teams to move faster while maintaining high standards for quality and reliability
• Own and evolve core backend systems and platforms that enable LLM-powered products at scale
• Drive the technical direction of complex, high-impact initiatives with significant ambiguity
• Partner closely with Product, ML, and Infrastructure teams to translate abstract requirements into robust engineering solutions
• Design and deliver scalable, reliable, and maintainable systems that power production-grade AI applications
• Raise the technical bar through mentorship, best practices, and architectural leadership
• Influence long-term platform and infrastructure roadmaps with a focus on scalability, maintainability, and developer velocity
• Execution & Delivery: Build, ship, and iterate on backend systems that support production-grade LLM applications. Deliver high-quality, maintainable code using a modern tech stack (e.g., Python, Postgres, Kubernetes, Elasticsearch)
• Architecture & Quality: Lead the architecture and design of resilient, scalable distributed systems. Establish and uphold best practices around system design, performance, observability, and reliability
• Cross-Functional Collaboration: Work closely with Product, ML, Data, and Infrastructure teams to scope, design, and deliver impactful solutions. Translate high-level product needs into clear technical plans and execution paths
• Ownership & Growth: Own projects end-to-end—from early design through deployment and continuous iteration. Mentor engineers and act as a force multiplier across the organization. Evaluate and introduce new tools and technologies to continuously improve platform capabilities