Software Engineer

Obsidian Security

About The Position

Founded in 2017, Obsidian Security was created to close a critical gap: securing the SaaS applications where modern business happens—platforms like Microsoft 365, Salesforce, and hundreds more. 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.

Requirements

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
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

Nice To Haves

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

Responsibilities

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