Full-time — DreamVR is looking for an AI-native Developer — an engineer who can independently turn product tasks into working systems. You will be responsible for the full development cycle: from understanding the task and defining requirements to design, implementation, production launch, and result evaluation. Years of experience and specific tech stack are secondary. The company values strong engineering thinking, real projects, independence, and the ability to quickly learn new technologies. AI agents are considered the primary development tool, so it is important not only to be able to use AI but also to understand the code, architecture, and results generated by the agents.
Salary: Based on interview results
Responsibilities
- Lead tasks from inception to completion: understand the context, define readiness criteria, choose a solution, implement it, and verify the result after launch.
- Independently refine product requirements, constraints, and architecture.
- Make engineering decisions and choose technologies and approaches based on the task.
- Work with AI agents as the primary development tool: decompose tasks, form context, set constraints, parallelize work, and verify results.
- Understand the entire system being created: code, architecture, data, infrastructure, and integrations.
- Quickly learn new technologies, stacks, and subject areas.
- Identify technical and product issues and independently bring useful improvements to completion.
Requirements
- Experience in creating real systems or products.
- Ability to independently lead a task from inception to production.
- Skills in system design and making technical decisions.
- Regular use of AI agents in development.
- Understanding of code and architecture generated with AI.
- Ability to verify the results of AI agent work and find errors in their solutions.
- Ability to quickly understand unfamiliar code, technologies, and subject areas.
- Strong engineering or mathematical foundation.
Benefits
- Work from task to result. Understand the context, define readiness criteria, choose a solution, implement it, and verify the result after launch.
- Independently refine requirements. The product goal and expected outcome are defined. The engineer independently translates them into requirements, constraints, architecture, and an implementation plan.
- Make engineering decisions. Choose approaches, technologies, and architecture based on the task. Be able to justify key decisions and understand their consequences.
- Work with AI agents as the primary development tool. Decompose tasks, form context, set constraints, parallelize work, and verify results.
- Understand the entire system being created. Understand code, architecture, data, infrastructure, and integrations as deeply as required by the task.
- Quickly learn new areas. Unfamiliar stacks, technologies, or subject areas should not significantly slow down work.
- Notice opportunities for improvement. Identify technical and product issues, assess their significance, and bring useful changes to completion.
