Build and own AI-native product features for legal operations, partnering directly with customers and cross-functional teams. The role suits a strong frontend or backend engineer who can move across the stack, make product decisions, and iterate rapidly.
195k – 350k/yr
HybridFullstack Engineering
About the role
Responsibilities
Build, ship, and maintain features for Eve's core product.
Collaborate with the team to understand user needs, define features, and determine implementation strategies.
Own backend systems—including architecture, implementation, deployment, monitoring, and iteration—or user-facing experiences, depending on expertise.
Collaborate across frontend, backend, machine learning, design, and product to bring complex features to life.
Design and build AI-native solutions that streamline legal operations.
Ship rapidly and iterate continuously based on user feedback.
Engage directly with customers to solve problems and improve the product.
Requirements
Proven track record of building high-quality products and owning projects as a primary decision-maker.
Strong depth in a primary area, such as frontend or backend engineering.
Frontend expertise in building intuitive, polished user experiences, or backend expertise in distributed systems, scalability, reliability, and performance tradeoffs.
Comfort working across the stack when needed.
Experience or strong interest in building with AI and creating production AI applications.
Ability to ship quickly and iterate based on real-world usage.
Strong collaboration skills and ability to work independently.
Compensation and Benefits
Base salary: $195,000–$350,000 USD
Competitive salary and equity
401(k) program with employer matching
Health, dental, vision, and life insurance
Short-term and long-term disability
Commuter benefits for in-office employees
Autonomous work environment
Workplace setup reimbursement
Telecommuting stipend
Flexible time off and holidays
Quarterly team gatherings
In-office perks for in-office employees
Skills
AIfrontend engineeringbackend engineeringFull-Stack DevelopmentDistributed SystemsScalabilityreliability engineeringPerformance OptimizationdeploymentMonitoringMachine Learningproduct development
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