Software Engineer

AI & Automation Design, build, and maintain AI-driven workflows that automate real business processes — LLM integration, MCP servers, agentic pipelines, and automated ops tooling. You own technical execution end-to-end, guided by product direction.

Engineering Operations Own monitoring, incident triage, backend production issues, cloud resource management, and back-office support for our field ops team. Autonomy to fix, automate, and improve as you go.

Cloud Infrastructure Manage and evolve our cloud infrastructure. Keep things running, scale what needs scaling, and build new infrastructure with a bias toward simplicity and maintainability. Stack-agnostic — we care about engineering judgment over familiarity with any specific toolset.

Full Stack Contribution Contribute across the stack when the team needs it — debugging front-end issues, supporting releases, or picking up work that doesn't fit neatly into a lane. Customer-facing app experience is a bonus, not the focus.

Stakeholder Communication Proactively communicate with cross-functional stakeholders who aren't engineers — operations leads, commercial teams, external partners. Explain what you're building, why it matters, and what the tradeoffs are without being asked.

Required Skills •

Cloud infrastructure experience — depth of understanding over specific stack

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AI agentic software development (LLM integration, MCP, tool-use)

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CI/CD pipeline management

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Comfortable in a Linux environment

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Full-stack capability — able to contribute across the stack

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Strong written and verbal communication (non-negotiable)