Staff Software Engineer, EvenUp

• 10+ years of software engineering experience, including at least 2 years in a Staff or equivalent senior technical leadership role
• Deep expertise in building and scaling distributed systems, frameworks, and internal platforms with a focus on reliability, observability, and performance
• Proven experience in driving complex technical initiatives across teams or domains, with strong system design skills and clear tradeoff thinking
• High standards for code quality, system design, and software architecture—along with a track record of mentoring others to meet those standards
• Strong proficiency in Python and/or experience in additional languages such as NodeJS, GoLang, Java or C++
• Clear, structured communication and the ability to influence stakeholders across engineering and product functions
• Experience working in fast-paced, high-growth environments—ideally in startups or early-stage companies

Desirable

• Our AI Platform team is looking for backend-focused Software Engineers who will join us in our mission to make LLMs more accessible and mainstream to the rest of our engineering teams
• The team has already built and released some of the best legal industry large language models that extract and summarize data from documents our clients provide
• This person will join a multi-disciplinary team of Data Scientists, Researchers and Software Engineers whose day-to-day work lies at the intersection of programming, LLM integration, and iterative experimentation
• This is a great opportunity for someone looking to take on complex engineering challenges in the field of generative AI and leverage the power of technology to bring fairness and accessibility to the legal system
• Deliver high-quality, maintainable code using a modern tech stack (e.g., Python, Postgres, Kubernetes, Elasticsearch) while introducing and evaluating new tools and technologies as appropriate
• Lead the architecture, design, and delivery of resilient, scalable systems and infrastructure that power production-grade applications including those based on large language models
• Set technical direction for complex projects with significant ambiguity, owning outcomes end-to-end from inception to deployment and iterative improvement
• Act as a force multiplier—mentoring engineers, setting engineering best practices, and elevating the technical bar across the organization
• Partner cross-functionally with Product, ML, and Infrastructure teams to translate abstract or high-level product needs into robust engineering solutions
• Influence platform and infrastructure roadmaps with a long-term view of scalability, maintainability, and developer velocity