Staff Software Engineer, Platform

EvenUp•San Francisco, CA

21h•Hybrid

About The Position

EvenUp is on a mission to close the justice gap using technology and AI. We empower personal injury lawyers and victims to get the justice they deserve. Our products enable law firms to secure faster settlements, higher payouts, and better outcomes for victims injured through no fault of their own in vehicle collisions, accidents, natural disasters, and more. We are one of the fastest-growing vertical SaaS companies in history, and we are just getting started. EvenUp is backed by top VCs, including Bessemer Venture Partners, Bain Capital Ventures, SignalFire, and Lightspeed. We are looking to expand our team with talented, driven, and collaborative individuals who seek to have a lasting impact. Learn more at www.evenuplaw.com. 🎥 Life as an Engineer at EvenUp About the Team 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.

Requirements

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

Nice To Haves

Experience working with AI/ML systems or LLM-powered applications
Exposure to AI platforms, developer enablement tooling, or ML-heavy environments
Background in legal tech, mission-driven products, or social-impact engineering
Prior startup or scale-up experience

Responsibilities

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
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)
Lead the architecture and design of resilient, scalable distributed systems.
Establish and uphold best practices around system design, performance, observability, and reliability
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
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