Senior Software Engineer
Engineer the core platform that powers our production-like development environments and AI-assisted developer workflows across all four EasyEnv products. Deep work in Python, Django, React, Linux, cloud infrastructure, and applied AI.
About the role
EasyEnv is the platform behind ephemeral, production-like Linux environments used by engineering and hiring teams worldwide. We orchestrate large fleets of virtual machines, deliver a full-featured terminal in the browser, record sessions for replay and review, and pair candidates and engineers with AI assistants that operate directly on their codebases.
We are hiring a senior engineer who is equally effective across a Django REST API, a Next.js application, an Ansible role, and a Celery task that coordinates VM lifecycle operations, and who is genuinely interested in applying modern AI techniques to assessment, code review, and developer productivity.
What you will do
- Own significant areas of the product end-to-end, from design and implementation through release, measurement, and iteration.
- Contribute across the stack: our Django REST API, Next.js frontend, Celery workers, and Ansible-based recipe system.
- Design and ship AI-driven capabilities that combine large language models with real Linux environments, including code review agents, candidate assistants, automated scoring, and new product surfaces.
- Improve the platform foundations: VM provisioning, networking through our NetBird mesh, observability, performance, and reliability.
- Provide thorough design and code review, uphold high engineering standards, and mentor engineers earlier in their careers.
What you will bring
- Five or more years of professional experience building production software, including substantial work in Python (Django or FastAPI) and modern React (TypeScript, Next.js).
- Strong Linux fundamentals, including comfort with systemd, networking, and command-line operations.
- Production experience with at least one major cloud provider (AWS, GCP, Azure, Hetzner, or Scaleway) and one orchestration approach (Kubernetes, Docker, or VM-based).
- Hands-on experience building with large language models, including tool use, retrieval-augmented generation, evaluations, prompt engineering, or agent-based workflows.
- A pragmatic, outcome-oriented approach to engineering: scoping work into focused, shippable increments and learning rapidly from production feedback.
Nice to have
- Experience operating Celery, Redis, or PostgreSQL at scale, or building VM provisioning pipelines (Proxmox, Packer, cloud-init).
- Background in developer tools, IDEs, terminal infrastructure, or technical assessment platforms.
- Open-source contributions, published technical writing, or conference experience.
What we offer
- Competitive base compensation, meaningful equity, and a transparent leveling and pay framework.
- Remote-first culture with asynchronous collaboration and flexible working hours.
- A mature product in active production use by engineering and talent teams across multiple industries.
- Modern hardware, an annual learning and development budget, and access to leading AI tools and tooling subscriptions.
- Comprehensive health, dental, and vision coverage where available, and a generous paid time off policy.
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