As a Software Engineer at Obsidian, you’ll:

Work across different parts of the product and codebase: backend services, APIs, data pipelines, integrations, product features, and internal tools. This is a good role for someone who likes variety and is comfortable learning a new area without needing everything mapped out in advance.

You might spend one week improving an ingestion service, the next building an API for a customer-facing workflow, and the next helping debug a production issue with another team. The work is practical, product-driven, and close to real customer problems.

What you’ll do

• Build and maintain product features across backend services, APIs, data systems, and user-facing workflows
• Work with product managers, designers, security researchers, and other engineers to ship useful, reliable software
• Contribute to services that process SaaS activity, identity data, permissions, alerts, and security findings
• Improve existing systems for performance, reliability, maintainability, and observability
• Write clear, well-tested code and participate in code reviews and design discussions
• Learn unfamiliar parts of the stack and help where the team needs you most
• Use AI-powered development tools thoughtfully while reviewing and validating the output

What’s in It for You

• Contribute to a core product used by enterprises worldwide
• Work on security problems across SaaS, identity, data, and AI usage
• Learn from experienced engineers across the US and UK teams
• Build depth in backend engineering while getting exposure to adjacent areas like data pipelines, detection systems, cloud infrastructure, and product engineering
• Be part of a fast-moving company where engineers are expected to own real problems

Required Skills & Experience

• 3+ years of experience in a software engineering role
• Proficiency in one or more modern programming languages such as Python, Go, TypeScript, or SQL
• Experience building backend services, APIs, data processing systems, or product features
• Familiarity with relational databases such as Postgres
• Understanding of software design principles, testing, debugging, and clean code practices
• Experience working with Git and participating in code reviews
• Comfort working in a collaborative team environment with changing requirements
• Curiosity and willingness to learn unfamiliar systems, tools, and problem domains

Desirable Experience

• Experience with cloud platforms such as AWS or GCP
• Exposure to containerization technologies such as Docker or Kubernetes
• Familiarity with event or streaming systems such as Kafka, Redis, or similar technologies
• Experience with observability tools such as Grafana, Prometheus, or similar platforms
• Exposure to CI/CD pipelines and deployment tooling
• Interest in security, SaaS platforms, identity, data protection, or detection systems
• Experience using AI-powered developer tools in day-to-day engineering work

AI Skills & AI-Native Engineering Expectations

As an AI-forward engineering organization, we expect engineers to use AI tools effectively and understand foundational AI concepts that are increasingly part of modern software development.

AI Engineering Capabilities

• Leverage AI tools to improve development speed while critically reviewing AI-generated output
• Understand core AI/ML concepts such as LLMs, embeddings, inference, evaluation, and vector databases
• Build software that is reliable, observable, secure, and maintainable in AI-assisted development workflows
• Show good judgment about where AI tools help, where they do not, and how to validate their output