Fullstack Engineer
Fullstack Engineers at AI companies build product features end-to-end across frontend, backend, and the integration layer between them. The day-to-day is recognizable full-stack work: designing API contracts, implementing UI alongside the services that power it, handling auth and data persistence, and owning features from product specification through production. Companies hire for this generalist profile in different contexts—at smaller companies, fullstack engineers often own most of a product surface; at larger companies, the role tends to bridge feature teams that would otherwise hand off across frontend/backend boundaries. AI-specific surfaces—integrating model APIs, building agent UIs, shipping LLM-backed features—are increasingly common but remain one type of feature work rather than the defining lens. These engineers typically sit within product engineering teams, collaborating with product, design, and ML or backend specialists as the architecture requires.
Skills
What companies are looking for in this role.
Designing and implementing end-to-end full-stack features across frontend, backend, and infrastructure layers
Building and scaling user-facing SaaS products with production reliability and performance requirements
Owning product features from conception through design, implementation, and iteration based on user feedback
Architecting backend systems and APIs including authentication, authorization, and data persistence
Building responsive and intuitive user interfaces with attention to user experience and interaction design
Debugging and troubleshooting issues across complex distributed systems and multiple layers of technology
Operating production systems including monitoring, alerting, incident response, and on-call responsibilities
Writing maintainable, testable, and well-documented code following established best practices
Designing and implementing platform abstractions and developer tooling to improve team productivity
Implementing observability and instrumentation including metrics, structured logging, and distributed tracing
Implementing enterprise-grade features including security, compliance, permissions, and scalability
Designing data models, schemas, and permission systems that scale with long-lived consequences for product evolution
Building integrations with third-party services and creating abstraction layers over vendor APIs
Understanding cloud infrastructure concepts and making informed buy-versus-build decisions for platform components
Integrating and working with AI models including prompt engineering, evaluation, and reliability assessment
Leveraging AI tools and language models to improve personal productivity and code quality
Building systems that handle model integration, observability, and graceful degradation for AI-powered features
Collaborating cross-functionally with product managers, designers, and other engineering teams to ship features
Working effectively in fast-paced, high-growth environments with rapidly changing priorities and competing deadlines
Technical leadership including mentoring engineers, driving architectural decisions, and raising code quality standards
Navigating ambiguous requirements and loosely defined problems with strong product instincts and scoping ability
Communicating technical concepts clearly to both technical and non-technical stakeholders
Taking ownership of 0-to-1 product development and shipping features quickly with bias for action
Technology
The tools and technologies that define this role.
Open Jobs
206 open Fullstack Engineer jobs across 69 companies.
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