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Laurel is an AI-powered time intelligence platform serving major professional services firms (EY, Aprio, Crowell & Moring, Frost Brown Todd). The company processes over 1 billion work activities annually, using proprietary machine learning to help accounting and law firms capture, analyze, and optimize time data—connecting it to business outcomes to increase profitability and improve client delivery.
As a Staff Software Engineer, you will have direct impact on engineering practices across the full stack (frontend and backend) and are expected to raise the bar for engineers around you. You'll work within a cross-functional pod (4–7 members) focused on specific customer needs and product areas, while collaborating across the entire engineering organization.
Key responsibilities include: architecting and developing efficient, reusable, and reliable code; working with product managers, designers, and engineers to define technical specifications and measures of success; identifying and resolving bottlenecks, bugs, and performance issues; providing technical guidance and mentorship to junior developers; staying current with industry trends and proactively suggesting improvements; implementing automated testing and CI/CD pipelines; and engaging directly with product and customer success teams to flesh out business requirements and system designs.
You will be expected to take ownership of your product areas, demonstrate initiative rather than waiting for direction, and actively engage with customers to understand their needs. Your input and opinions on how things should be built and why will be highly valued.
Required qualifications: Bachelor's degree in Computer Science, Engineering, or related field (or equivalent practical experience); 8+ years of professional software development experience with a focus on full-stack development; strong understanding of React, TypeScript, JavaScript, HTML, and CSS on the frontend; strong understanding of TypeScript, Node.js, messaging queues (AWS SQS), MongoDB, and NestJS on the backend; experience using AI in day-to-day work; strong analytical and problem-solving skills; excellent communication and collaboration abilities; and a customer mindset with proven ability to engage with customers.
Nice-to-have skills include familiarity with Next.js, TailwindCSS, component libraries, Python (Django, FastAPI, Flask), Airflow, and PostgreSQL. The ideal candidate will have deep knowledge and strongly-held opinions about best practices, patterns, code quality, and performance optimization—and be ready to mentor others on these topics.
