Software Engineer
Indexed description
Backed by top investors including Greylock, Norwest Venture Partners, and IVP, we’ve built a complete SaaS security platform to reduce risk, detect and respond to threats, and prevent breaches at the source. Our team includes leaders who helped define the categories of endpoint and identity security at CrowdStrike, Okta, Cylance, and Carbon Black.
Now, we’re transforming how SaaS is secured—in the era of agentic AI.
Today, Obsidian is trusted by global enterprises like Snowflake, T-Mobile, and Pure Storage. We protect more than 200 organizations across North America, Europe, the Middle East, Southeast Asia, Australia, and New Zealand—including many of the world’s largest Fortune 1000 and Global 2000 companies.
With strong global momentum, a growing partner ecosystem including SentinelOne, Databricks, and Google Cloud, and a major fundraise on the horizon, we’re scaling quickly toward long-term growth and IPO readiness. Join us as we define the future of SaaS security!
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
- 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
- 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
- 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
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
Base Salary Range: $131,000 USD - $152,000 USD
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