Software Engineer, Full Stack — Dots
$347k - $385k • Remote • New York City • FullTime
Posted 2h ago
Job Location
New York City
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
Dots is building personal AI agents designed to help users make progress on their goals, even when they are not actively using the system. These agents are capable of learning user preferences, maintaining context across interactions, operating across different applications, and utilizing cloud computing resources to execute tasks. The engineering team collaborates closely with product, design, and research to transform cutting-edge model capabilities into practical, everyday user experiences. Engineers play a crucial role in shaping both the product itself and the underlying systems, from initial prototyping through to launch and ongoing iteration.
Responsibilities
- Build and launch features across web interfaces, APIs, backend services, and data models.
- Create coherent workflows for task creation, progress updates, agent feedback, and results that persist across sessions and devices.
- Translate emerging model capabilities into product prototypes in collaboration with research, product, and design partners.
- Design clear interfaces between product surfaces and agent execution systems.
- Improve performance and reliability across the entire stack, addressing user-facing latency and recovery from partial failures.
- Own projects from early exploration through architecture, implementation, launch, and iteration based on user feedback.
- Help establish technical direction, testing practices, and observability as the product grows.
Requirements
- Significant experience building and shipping products across frontend and backend systems.
- Ability to work comfortably across user interfaces, service design, APIs, and data modeling.
- Strong product instincts and a focus on making complex capabilities understandable to users.
- Experience taking ambiguous ideas from concept to production, making practical tradeoffs between iteration speed and long-term maintainability.
- Understanding of asynchronous workflows and the ability to reason about state, consistency, and failure across system boundaries.
- Effective collaboration with design, product, research, and engineering partners.
- Experience owning complex engineering projects and guiding other engineers in making sound technical decisions.
- Experience launching new consumer products, building agent or workflow applications, or working in small teams with broad engineering ownership is particularly relevant.
- Prior experience with AI or machine learning is helpful but not required.