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Geordie is building enterprise tooling for AI agent visibility, governance, and risk management. As a Senior Software Engineer, you will help build the platform that enterprises use to understand and govern their AI agents in production.
You will work directly on customer problems: understanding their needs, designing solutions collaboratively, and shipping improvements weekly. The role spans backend and frontend development across Java, Python, Node, and Rust ecosystems, with cloud-native infrastructure on AWS. The team dogfoods its own product extensively and uses AI agents as part of daily workflows.
Key responsibilities include:
- Building and shipping product improvements that solve real customer problems
- Working across the full stack, learning new parts as needed
- Collaborating directly with customers and go-to-market teams to understand needs
- Designing and iterating solutions with designers, engineers, stakeholders, and customers
- Improving systems through refactors, reducing operational toil, and automating workflows
- Owning reliability through instrumentation, observability, and meaningful alerting
- Improving infrastructure, delivery pipelines, and deployment automation
- Helping shape technical direction of the product and platform
- Exploring how agents are changing software development and operations
- Participating in shared on-call and in-hours support rotation
The engineering culture is influenced by Extreme Programming: collaborative by default, close to customers, iterating in small steps, and shipping at a sustainable pace. The team pairs often, shares ownership, and relies on automated tests and observability.
Requirements:
- Fluency in at least one of Java, Python, TypeScript, or Rust (or similar language) with ability to get productive quickly in unfamiliar codebases
- Demonstrated delivery of significant production software, both greenfield and within existing systems
- Experience being on-call for critical systems, debugging under pressure, and improving systems afterwards
- Understanding of secure software development and common vulnerabilities
- Comfort with cloud infrastructure (AWS), including infrastructure as code, CI/CD, and containers
- Knowledge of useful observability: meaningful metrics, logs, traces, and alerts
- Ability to take ownership in fast-moving environments where product, processes, and tooling are evolving
- Experience using AI agents as part of work (pairing, automation, workflow orchestration) with judgment about when they are useful
