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 building end-to-end product features from conception to production deployment
Architecting scalable backend systems and APIs that handle complex business logic and data flows
Building responsive and performant user interfaces with attention to user experience and accessibility
Building and maintaining distributed systems with high reliability, correctness, and data integrity
Architecting systems for deployment, scaling, and operations in cloud environments
Optimizing application performance through profiling, caching, and architectural improvements
Designing and implementing testing strategies including unit tests, integration tests, and end-to-end testing
Designing data models and APIs that abstract complex domain logic for external consumers
Managing technical debt and driving continuous architectural improvements
Implementing observability, monitoring, and alerting for production systems
Building rapid prototypes and MVPs to validate product ideas quickly
Designing intuitive workflows and interaction patterns for complex internal tools
Implementing security best practices including authentication, authorization, and privacy controls
Building real-time systems and websocket-based communication for live data updates
Working with heterogeneous data sources and building data integration pipelines
Building AI-native product features that leverage language models and machine learning capabilities
Implementing experimentation frameworks and A/B testing to measure product impact data-driven iteration
Designing developer experience improvements and developer-facing platforms and tooling
Leveraging AI coding assistants to accelerate development velocity and code generation
Building no-code or low-code platforms that enable non-technical users to configure workflows
Collaborating across product, design, and engineering teams to translate requirements into technical solutions
Taking ownership of product outcomes and making autonomous decisions about technical direction
Adapting quickly to new technologies and problem domains with self-directed learning
Communicating technical decisions and trade-offs clearly to non-technical stakeholders
Mentoring junior engineers and fostering team technical excellence through code review
Technology
The tools and technologies that define this role.
Open Jobs
242 open Fullstack Engineer jobs across 86 companies.
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